Affiliations
Department of Pediatrics, University of Cincinnati College of Medicine
Division of Emergency Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio
Given name(s)
Lilliam
Family name
Ambroggio
Degrees
PhD, MPH

Antibiotics for Aspiration Pneumonia in Neurologically Impaired Children

Article Type
Changed
Tue, 06/30/2020 - 09:35

Neurologic impairment (NI) encompasses static and progressive diseases of the central and/or peripheral nervous systems that result in functional and intellectual impairments.1 While a variety of neurologic diseases are responsible for NI (eg, hypoxic-ischemic encephalopathy, muscular dystrophy), consequences of these diseases extend beyond neurologic manifestations.1 These children are at an increased risk for aspiration of oral and gastric contents given their common comorbidities of dysphagia, gastroesophageal reflux, impaired cough, and respiratory muscle weakness.2 While aspiration may manifest as a self-resolving pneumonitis, the presence of oral or enteric bacteria in aspirated material may result in the development of bacterial pneumonia. Children with NI hospitalized with aspiration pneumonia have higher complication rates, longer and costlier hospitalizations, and higher readmission rates when compared with children with nonaspiration pneumonia.3

While pediatric aspiration pneumonia is commonly attributed to anaerobic bacteria, this is largely based on extrapolation from epidemiologic studies that were conducted in past decades.4-8 A single randomized controlled trial found that penicillin and clindamycin, antimicrobials with similar antimicrobial activity against anaerobes, to be equally effective.9 However, the recent literature emphasizes the polymicrobial nature of aspiration pneumonia in adults, with the common isolation of Gram-negative enteric bacteria.10 Further, while Pseudomonas aeruginosa is often identified in respiratory cultures from children with NI and chronic respiratory insufficiency,11,12 the significance of P. aeruginosa in lower airways remains unclear.

We designed this study to compare hospital outcomes associated with the most commonly prescribed empiric antimicrobial therapies for aspiration pneumonia in children with NI.

MATERIALS AND METHODS

Study Design and Data Source

This multicenter, retrospective cohort study used the Pediatric Health Information System (PHIS) database. PHIS, an administrative database of 50 not-for-profit tertiary care pediatric hospitals, contains data regarding patient demographics, diagnoses and procedures, and daily billed resource utilization, including laboratory and imaging studies. Data quality and reliability are assured through the Children’s Hospital Association (CHA; Lenexa, Kansas) and participating hospitals. Due to incomplete data through the study period and data quality issues, six hospitals were excluded.

STUDY POPULATION

Inclusion Criteria

Children 1-18 years of age who were discharged between July 1, 2007 and June 30, 2015 were included if they had a NI diagnosis,1 a principal diagnosis indicative of aspiration pneumonia (507.x),3,13,14 and received antibiotics in the first two calendar days of admission. NI was determined using previously defined International Classification of Diseases, Ninth Revision-Clinical Modification (ICD-9-CM) diagnosis codes.1 We only included children who received antibiotics in the first two calendar days of admission to minimize the likelihood of including children admitted for other reasons who acquired aspiration pneumonia after hospitalization. For children with multiple hospitalizations, one admission was randomly selected for inclusion to minimize weighting results toward repeat visits.

 

 

Exclusion Criteria

Children transferred from another hospital were excluded as records from their initial presentation, including treatment and outcomes, were not available. We also excluded children with tracheostomy15,16 or chronic ventilator dependence,17 those with a diagnosis of human immunodeficiency virus or tuberculosis, and children who received chemotherapy during hospitalization given expected differences in etiology, treatment, and outcomes.18

Exposure

The primary exposure was antibiotic therapy received in the first two days of admission. Antibiotics were classified by their antimicrobial spectra of activity as defined by The Sanford Guide to Antimicrobial Therapy19 against the most commonly recognized pathogens of aspiration pneumonia: anaerobes, Gram-negatives, and P. aeruginosa (Appendix Table 1).10,20 For example, penicillin G and clindamycin were among the antibiotics classified as providing anaerobic coverage alone, whereas ceftriaxone was classified as providing Gram-negative coverage alone and ampicillin-sulbactam or as combination therapy with clindamycin and ceftriaxone were classified as providing anaerobic and Gram-negative coverage. Piperacillin-tazobactam and meropenem were classified as providing anaerobic, Gram-negative, and P. aeruginosa coverage. We excluded antibiotics that do not provide coverage against anaerobes, Gram-negative, or P. aeruginosa (eg, ampicillin, azithromycin) or that provide coverage against Gram-negative and P. aeruginosa, but not anaerobes (eg, cefepime, tobramycin), as these therapies were prescribed for <5% of the cohort. We chose not to examine the coverage for Streptococcus pneumonia or Staphylococcus aureus as antibiotics included in this analysis covered these bacteria for 99.9% of our cohort.

OUTCOMES

Outcomes included acute respiratory failure during hospitalization, intensive care unit (ICU) transfer, and hospital length of stay (LOS). Acute respiratory failure during hospitalization was defined as the presence of Clinical Transaction Classification (CTC) or ICD-9 procedure code for noninvasive or invasive mechanical ventilation on day two or later of hospitalization, with or without the need for respiratory support on day 0 or day 1 (Appendix Table 2). Given the variability in hospital policies that may drive ICU admission criteria for complex patients, our outcome of ICU transfer was defined as the requirement for ICU level care on day two or later of hospitalization without ICU admission. Acute respiratory failure and ICU care occurring within the first two hospital days were not classified as outcomes because these early events likely reflect illness severity at presentation rather than outcomes attributable to treatment failure; these were included as markers of severity in the models.

Patient Demographics and Clinical Characteristics

Demographic and clinical characteristics that might influence antibiotic choice and/or hospital outcomes were assessed. Clinical characteristics included complex chronic conditions,21-23 medical technology assistance,24 performance of diagnostic testing, and markers of severe illness on presentation. Diagnostic testing included bacterial cultures (blood, respiratory, urine) and chest radiograph performance in the first two days of hospitalization. Results of diagnostic testing are not available in the PHIS. Illness severity on presentation included acute respiratory failure, pleural drainage, receipt of vasoactive agents, and transfusion of blood products in the first two days of hospitalization (Appendix Table 2).17,25,26

STASTICAL ANALYSIS

Continuous data were described with median and interquartile ranges (IQR) due to nonnormal distribution. Categorical data were described with frequencies and percentages. Patient demographics, clinical characteristics, and hospital outcomes were stratified by empiric antimicrobial coverage and compared using chi-square and Kruskal–Wallis tests as appropriate.

 

 

Generalized linear mixed-effects models with random hospital intercepts were derived to assess the independent effect of antimicrobial spectra of activity on outcomes of acute respiratory failure, ICU transfer, and LOS while adjusting for important differences in demographic and clinical characteristics. LOS had a nonnormal distribution. Thus, we used an exponential distribution. Covariates were chosen a priori given the clinical and biological relevance to exposure and outcomes—age, presence of complex chronic condition diagnoses, the number of complex chronic conditions, technology dependence, the performance of diagnostic tests on presentation, and illness severity on presentation. ICU admission was included as a covariate in acute respiratory failure and LOS outcome models. The results of the model for acute respiratory failure and ICU transfer are presented as adjusted odds ratios (OR) with a 95% CI. LOS results are presented as adjusted rate ratios (RR) with 95% CI.

All analyses were performed with SAS 9.3 (SAS Institute, Cary, North Carolina). P values <.05 were considered statistically significant. Cincinnati Children’s Hospital Medical Center Institutional Review Board considered this deidentified dataset study as not human subjects research.

RESULTS

Study Cohort

At the 44 hospitals included, 4,812 children with NI hospitalized with the diagnosis of aspiration pneumonia met the eligibility criteria. However, 79 received antibiotics with the spectra of activity not examined, leaving 4,733 children in our final analysis (Appendix Figure). Demographic and clinical characteristics of the study cohort are shown in Table 1. Median age was five years (interquartile range [IQR]: 2-11 years). Most subjects were male (53.9%), non-Hispanic white (47.9%), and publicly insured (63.6%). There was a slight variation in the distribution of admissions across seasons (spring 31.6%, summer 19.2%, fall 21.3%, and winter 27.9%). One-third of children had four or more comorbid CCCs (complex chronic conditions; 34.2%). The three most common nonneurologic CCC diagnosis categories were gastrointestinal (63.1%), congenital and/or genetic defects (36.9%), and respiratory (8.9%). Assistance with medical technologies was also common (82%)—particularly gastrointestinal (63.1%) and neurologic/neuromuscular (9.8%) technologies. The vast majority of children (92.5%) had either a chest radiograph (90.5%), respiratory viral study (33.7%), or respiratory culture (10.0%) obtained on presentation. A minority required noninvasive or invasive respiratory support (25.4%), vasoactive agents (8.9%), blood products (1.2%), or pleural drainage (0.3%) in the first two hospital days.

Spectrum of Antimicrobial Coverage

Most children (57.9%) received anaerobic and Gram-negative coverage; 16.2% received anaerobic, Gram-negative and P. aeruginosa coverage; 15.3% received anaerobic coverage alone; and 10.6% received Gram-negative coverage alone. Empiric antimicrobial coverage varied substantially across hospitals: anaerobic coverage was prescribed for 0%-44% of patients; Gram-negative coverage was prescribed for 3%-26% of patients; anaerobic and Gram-negative coverage was prescribed for 25%-90% of patients; and anaerobic, Gram-negative, and P. aeruginosa coverage was prescribed for 0%-65% of patients (Figure 1).

There were several important differences between treatment groups (Table 1). Children receiving anaerobic, Gram-negative, and P. aeruginosa coverage were older, more likely to have certain CCCs (respiratory, gastrointestinal, and malignancy), have ≥4 CCCs, and require assistance with medical technologies (respiratory, gastrointestinal) compared with all other treatment groups. They were also more likely to have respiratory viral testing and bacterial cultures obtained and to have markers of severe illness on presentation.

 

 

Outcomes

Acute Respiratory Failure

One-quarter (25.4%) of patients had acute respiratory failure on presentation; 22.5% required respiratory support (continued from presentation or were new) on day two or later of hospitalization (Table 2). In the adjusted analysis, children receiving Gram-negative coverage alone had two-fold greater odds (OR 2.15, 95% CI: 1.41-3.27) and children receiving anaerobic and Gram-negative coverage had 1.6-fold greater odds (OR 1.65, 95% CI: 1.19-2.28), of respiratory failure during hospitalization compared with those receiving anaerobic coverage alone (Figure 2). Odds of respiratory failure during hospitalization did not significantly differ for children receiving anaerobic, Gram-negative, and P. aeruginosa coverage compared with those receiving anaerobic coverage alone.

ICU Transfer

Nearly thirty percent (29.0%) of children required ICU admission, with an additional 3.8% requiring ICU transfer following admission (Table 2). In the multivariable analysis, the odds of an ICU transfer were greater for children receiving Gram-negative coverage alone (OR 1.80, 95% CI: 1.03-3.14) compared with those receiving anaerobic coverage alone. There was no statistical difference in ICU transfer for those receiving anaerobic and Gram-negative coverage (with or without P. aeruginosa coverage) compared with those receiving anaerobic coverage alone (Figure 2).

Length of Stay

Median hospital LOS for the total cohort was five days (IQR: 3-9 days; Table 2). In the multivariable analysis, children receiving Gram-negative coverage alone had a longer LOS (RR 1.28; 95% CI: 1.16-1.41) compared with those receiving anaerobic coverage alone, whereas children receiving anaerobic, Gram-negative, and P. aeruginosa coverage had a shorter LOS (RR 0.83; 95% CI: 0.76-0.90) than those receiving anaerobic coverage alone (Figure 2). There was no statistical difference in the LOS between children receiving anaerobic and Gram-negative coverage and those receiving anaerobic coverage alone.

DISCUSSION

In this multicenter study of children with NI hospitalized with aspiration pneumonia, we found substantial variation in empiric antimicrobial coverage for children with aspiration pneumonia. When comparing outcomes across groups, children who received anaerobic and Gram-negative coverage had outcomes similar to children who received anaerobic therapy alone. However, children who did not receive anaerobic coverage (ie, Gram-negative coverage alone) had worse outcomes, most notably a greater than two-fold increase in the odds of experiencing acute respiratory failure during hospitalization when compared with children receiving anaerobic therapy. These findings support prior literature that has highlighted the importance of anaerobic therapy in the treatment of aspiration pneumonia. The benefit of antibiotics targeting Gram-negative organisms, in addition to anaerobes, remains uncertain.

The variability in empiric antimicrobial coverage likely reflects the paucity of available information on oral and/or enteric bacteria required to identify them as causative organisms in aspiration pneumonia. In part, this problem is due to the difficulty in obtaining adequate sputum for culture from pediatric patients.27 While it may be more feasible to obtain tracheal aspirates for respiratory culture in children with a tracheostomy, interpretation of culture results remains challenging because the lower airways of children with tracheostomy are commonly colonized with bacterial pathogens.28 Thus, physicians are often left to choose empiric antimicrobial coverage with inadequate supporting evidence.29 Although the polymicrobial nature of aspiration pneumonia is well recognized in adult and pediatric literature,10,30 it is less clear which organisms are of pathological significance and require treatment.

The treatment standard for aspiration pneumonia has long included anaerobic therapy.29 The worse outcomes of children not receiving anaerobic therapy (ie, Gram-negative coverage alone) compared with children who received anaerobic therapy support the continued importance of anaerobic therapy in the treatment of aspiration pneumonia for hospitalized children with NI. The role of antibiotics covering Gram-negative organisms is less clear. Recent studies suggest the role of anaerobes is overemphasized in the etiology and treatment of aspiration pneumonia.10,29,31-38 Multiple studies on aspiration pneumonia bacteriology in hospitalized adults have demonstrated a predominance of Gram-negative organisms (ranging from 37%-71% of isolates identified on respiratory culture) and a relative scarcity of anaerobes (ranging from 0%-16% of isolates).31-37 A prospective study of 50 children hospitalized with clinical and radiographic evidence of pneumonia with known aspiration risk (eg, neuromuscular disease or dysphagia) found that ~80% of 163 bacterial isolates were Gram-negative.38 However, this study included repeat cultures from the same children, and thus, may overestimate the prevalence of Gram-negative organisms. In our study, children who received both anaerobic and Gram-negative therapy had no differences in ICU transfer or LOS but did experience higher odds of acute respiratory failure. As these results may be due to unmeasured confounding, future studies should further explore the necessity of Gram-negative coverage in addition to anaerobic coverage in this population.

While these recent studies may seem to suggest that anaerobic coverage is not necessary for aspiration pneumonia, there are important limitations worth noting. First, these studies used a variety of sampling techniques. While organisms grown from samples obtained via bronchoalveolar lavage31-34,36 are likely pathogenic, those grown from tracheal or oral samples obtained via percutaneous transtracheal aspiration,34 a protected specimen brush,34,36,37 or expectorated sputum35,38 may not represent lower airway organisms. Second, anaerobic cultures were not obtained in all studies.31,34,38 Anaerobic organisms are difficult to isolate using traditional clinical specimen collection techniques and aerobic culture media.18 Furthermore, anaerobes are not easily recovered from lung infections after the receipt of antibiotic therapy.39 Details regarding pretreatment, which are largely lacking from these studies, are necessary to interpret the relative scarcity of anaerobes on respiratory culture. Finally, caution should be taken when extrapolating the results of studies focused on the etiology and treatment of aspiration pneumonia in elderly adults to children. Our results, particularly in the context of the limitation of these more recent studies, suggest that the role of anaerobes has been underestimated.

Recent studies examining populations of children with cerebral palsy and/or tracheostomy have emphasized the high rates of carriage and infection rates with Gram-negative and drug-resistant bacteria; in particular, P. aeruginosa accounts for 50%-72% of pathogenic bacteria.11,12,38,40These studies note the generally poor outcomes of children with P. aeruginosa—including multiple and longer hospitalizations, frequent readmissions, and the increased severity of pneumonia, including the need for ICU admission, pleural effusions, the need for intubation, and mortality.11,12,38,40,41 In our study, nearly 35% of children who received anaerobic, Gram-negative, and P. aeruginosa coverage experienced acute respiratory failure during hospitalization compared with 20% of children who received other therapies. While these results might seem to suggest that broader spectrum therapy is harmful, they must be interpreted in the context of important population differences; children who received a combination of anaerobic, Gram-negative, and P. aeruginosa coverage had greater medical complexity and greater severity of illness on presentation. Such factors may provide the reason for the appropriate prescription of antipseudomonal antibiotics (eg, history of tracheostomy colonization or infection, long-term care facility resident).42 When we controlled for population differences, children who received antipseudomonal therapy had a significantly shorter LOS and no differences in outcomes of acute respiratory failure or ICU transfer compared with those receiving anaerobic therapy alone. This result suggests that worse outcomes were associated with antipseudomonal therapy on unadjusted analyses resulting from underlying medical complexity and illness severity rather than from colonization or infection with P. aeruginosa.

Our multicenter observational study has several limitations. We used diagnosis codes to identify patients with aspiration pneumonia. As validated clinical criteria for the diagnosis of aspiration pneumonia do not exist, clinicians may assign a diagnosis of and treatment for aspiration pneumonia by subjective suspicion based on a child’s severe NI or illness severity on presentation leading to selection bias. Although administrative data are not able to verify pneumonia type with absolute certainty, we previously demonstrated that the differences in the outcomes of children with aspiration and nonaspiration pneumonia diagnosis codes persist after accounting for the complexity that might influence the diagnosis.3It is also possible that the diagnosis of aspiration pneumonia was not made upon admission for a subset of patients leading to misclassification of exposure. Some children may have had aspiration pneumonia on admission but were not assigned that diagnosis or treated for presumed aspiration pneumonia until later in the hospital course as they demonstrated treatment failure or clinical worsening. It is also possible that some children had an aspiration event during hospitalization that developed into aspiration pneumonia. We attempted to adjust for medical complexity and illness severity through multivariable adjustment based on the diagnosis and procedure codes, as well as the laboratory testing performed. However, unmeasured or residual confounding may remain as administrative data are not equipped to distinguish detailed functional status (eg, ability to cough, chest wall strength) or illness severity (eg, respiratory distress) that might influence antibiotic selection and/or outcomes.

Frthermore, we were unable to account for laboratory, microbiology, or radiology test results, and other management practices (eg, frequency of airway clearance, previous antimicrobial therapy) that may influence outcomes. Future studies should certainly include an examination of the concordance of the antibiotics prescribed with causative organisms, as this undoubtedly affects patient outcomes. Other outcomes are important to examine (eg, time to return to respiratory baseline), but we were unable to do so, given the lack of clinical detail in our database. We randomly selected a single hospitalization for children with multiple admissions; alternative methods could have different results. Although children with NI predominately use children’s hospitals,1 results may not be generalizable.

 

 

CONCLUSION

These findings support prior literature that has highlighted the important role anaerobic therapy plays in the treatment of aspiration pneumonia in children with NI. In light of the limitations of our study design, we believe that rigorous clinical trials comparing anaerobic with anaerobic and Gram-negative therapy are an important and necessary next step to determine the optimal treatment for aspiration pneumonia in this population.

Disclosures

The authors do not have any financial relationships relevant to this article to disclose.

Funding

Dr. Thomson was supported by the Agency for Healthcare Research and Quality (AHRQ) under award number K08HS025138. Dr. Ambroggio was supported by the National Institute for Allergy and Infectious Diseases (NIAID) under award number K01AI125413. The content is solely the responsibility of the authors and does not necessarily represent the official views of the AHRQ or NIAID.

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References

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10. DiBardino DM, Wunderink RG. Aspiration pneumonia: a review of modern trends. J Crit Care. 2015;30(1):40-48. https://doi.org/10.1016/j.jcrc.2014.07.011.
11. Gerdung CA, Tsang A, Yasseen AS, 3rd, Armstrong K, McMillan HJ, Kovesi T. Association between chronic aspiration and chronic airway infection with Pseudomonas aeruginosa and other Gram-negative bacteria in children with cerebral palsy. Lung. 2016;194(2):307-314. https://doi.org/10.1007/s00408-016-9856-5.
12. Thorburn K, Jardine M, Taylor N, Reilly N, Sarginson RE, van Saene HK. Antibiotic-resistant bacteria and infection in children with cerebral palsy requiring mechanical ventilation. Pedr Crit Care Med. 2009;10(2):222-226. https://doi.org/10.1097/PCC.0b013e31819368ac.
13. Lanspa MJ, Jones BE, Brown SM, Dean NC. Mortality, morbidity, and disease severity of patients with aspiration pneumonia. J Hosp Med. 2013;8(2):83-90. https://doi.org/10.1002/jhm.1996.
14. Lanspa MJ, Peyrani P, Wiemken T, Wilson EL, Ramirez JA, Dean NC. Characteristics associated with clinician diagnosis of aspiration pneumonia: a descriptive study of afflicted patients and their outcomes. J Hosp Med. 2015;10(2):90-96. https://doi.org/10.1002/jhm.2280.
15. Berry JG, Graham RJ, Roberson DW, et al. Patient characteristics associated with in-hospital mortality in children following tracheotomy. Arch Dis Child. 2010;95(9):703-710.
16. Berry JG, Graham DA, Graham RJ, et al. Predictors of clinical outcomes and hospital resource use of children after tracheotomy. Pediatrics. 2009;124(2):563-572. https://doi.org/10.1136/adc.2009.180836.
17. Balamuth F, Weiss SL, Hall M, et al. Identifying pediatric severe sepsis and septic shock: Accuracy of diagnosis codes. J Pediatr. 2015;167(6):1295-1300 e1294. https://doi.org/10.1016/j.jpeds.2015.09.027.
18. American Academy of Pediatrics., Pickering LK, American Academy of Pediatrics. Committee on Infectious Diseases. In: Red book : 2012 report of the Committee on Infectious Diseases. 29th ed. Elk Grove Village: American Academy of Pediatrics; 2012.
19. Gilbert DN. The Sanford Guide to Antimicrobial Therapy 2014. 44th ed. Sperryville: Antimicrobial Therapy, Inc; 2011.
20. Marik PE. Aspiration pneumonitis and aspiration pneumonia. N Engl J Med. 2001;344(9):665-671. https://doi.org/10.1056/NEJM200103013440908.
21. Feudtner C, Feinstein JA, Zhong W, Hall M, Dai D. Pediatric complex chronic conditions classification system version 2: updated for ICD-10 and complex medical technology dependence and transplantation. BMC Pediatrics. 2014;14:199. https://doi.org/10.1186/1471-2431-14-199.
22. Feudtner C, Hays RM, Haynes G, Geyer JR, Neff JM, Koepsell TD. Deaths attributed to pediatric complex chronic conditions: national trends and implications for supportive care services. Pediatrics. 2001;107(6):E99. https://doi.org/10.1542/peds.107.6.e99.
23. Feinstein JA, Russell S, DeWitt PE, Feudtner C, Dai D, Bennett TD. R package for pediatric complex chronic condition classification. JAMA Pediatr. 2018;172(6):596-598. https://doi.org/10.1001/jamapediatrics.2018.0256.
24. Berry JG, Hall DE, Kuo DZ, Cohen E, Agrawal R, Feudtner C, Hall M, Kueser J, Kaplan W, Neff J. Hospital utilization and characteristics of patients experiencing recurrent readmissions within children’s hospitals. JAMA. 2011;305(7):682-690. https://doi.org/10.1001/jama.2011.122.
25. Shah SS, Hall M, Newland JG, et al. Comparative effectiveness of pleural drainage procedures for the treatment of complicated pneumonia in childhood. J Hosp Med. 2011;6(5):256-263. https://doi.org/10.1002/jhm.872.
26. Child Health Corporation of America. CTC™ 2010 Code Structure: Module 5 Clinical Services. 2010 January 4; Available at https://sharepoint.chca.com/CHCAForums/PerformanceImprovement/PHIS/Reference Library/CTC Resources/Forms/AllItems.aspx Version: Modified.
27. Bradley JS, Byington CL, Shah SS, et al. The management of community-acquired pneumonia in infants and children older than 3 months of age: clinical practice guidelines by the Pediatric Infectious Diseases Society and the Infectious Diseases Society of America. Clin Infect Dis. 2011;53(7):e25-76. https://doi.org/10.1093/cid/cir531.
28. Brook I. Bacterial colonization, tracheobronchitis, and pneumonia following tracheostomy and long-term intubation in pediatric patients. Chest. 1979;76(4):420-424.
29. Waybright RA, Coolidge W, Johnson TJ. Treatment of clinical aspiration: a reappraisal. Am J Health Syst Pharm. 2013;70(15):1291-1300. https://doi.org/10.2146/ajhp120319.
30. Brook I, Finegold SM. Bacteriology of aspiration pneumonia in children. Pediatrics. 1980;65(6):1115-1120.
31. Wei C, Cheng Z, Zhang L, Yang J. Microbiology and prognostic factors of hospital- and community-acquired aspiration pneumonia in respiratory intensive care unit. Am J Infect Control. 2013;41(10):880-884. https://doi.org/10.1016/j.ajic.2013.01.007.
32. El-Solh AA, Pietrantoni C, Bhat A, et al. Microbiology of severe aspiration pneumonia in institutionalized elderly. Am J Respir Crit Care Med. 2003;167(12):1650-1654. https://doi.org/10.1164/rccm.200212-1543OC.
33. Tokuyasu H, Harada T, Watanabe E, et al. Effectiveness of meropenem for the treatment of aspiration pneumonia in elderly patients. Intern Med. 2009;48(3):129-135. https://doi.org/10.2169/internalmedicine.48.1308.
34. Ott SR, Allewelt M, Lorenz J, Reimnitz P, Lode H, German Lung Abscess Study Group. Moxifloxacin vs ampicillin/sulbactam in aspiration pneumonia and primary lung abscess. Infection. 2008;36(1):23-30. https://doi.org/10.1007/s15010-007-7043-6.
35. Kadowaki M, Demura Y, Mizuno S, et al. Reappraisal of clindamycin IV monotherapy for treatment of mild-to-moderate aspiration pneumonia in elderly patients. Chest. 2005;127(4):1276-1282. https://doi.org/10.1016/j.chest.2017.05.019.
36. Marik PE, Careau P. The role of anaerobes in patients with ventilator-associated pneumonia and aspiration pneumonia: a prospective study. Chest. 1999;115(1):178-183. https://doi.org/10.1378/chest.115.1.178.
37. Mier L, Dreyfuss D, Darchy B, et al. Is penicillin G an adequate initial treatment for aspiration pneumonia? A prospective evaluation using a protected specimen brush and quantitative cultures. Intensive Care Med. 1993;19(5):279-284. https://doi.org/10.1007/bf01690548.
38. Ashkenazi-Hoffnung L, Ari A, Bilavsky E, Scheuerman O, Amir J, Prais D. Pseudomonas aeruginosa identified as a key pathogen in hospitalised children with aspiration pneumonia and a high aspiration risk. Acta Paediatr. 2016;105(12):e588-e592. https://doi.org/10.1111/apa.13523.
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Related Articles

Neurologic impairment (NI) encompasses static and progressive diseases of the central and/or peripheral nervous systems that result in functional and intellectual impairments.1 While a variety of neurologic diseases are responsible for NI (eg, hypoxic-ischemic encephalopathy, muscular dystrophy), consequences of these diseases extend beyond neurologic manifestations.1 These children are at an increased risk for aspiration of oral and gastric contents given their common comorbidities of dysphagia, gastroesophageal reflux, impaired cough, and respiratory muscle weakness.2 While aspiration may manifest as a self-resolving pneumonitis, the presence of oral or enteric bacteria in aspirated material may result in the development of bacterial pneumonia. Children with NI hospitalized with aspiration pneumonia have higher complication rates, longer and costlier hospitalizations, and higher readmission rates when compared with children with nonaspiration pneumonia.3

While pediatric aspiration pneumonia is commonly attributed to anaerobic bacteria, this is largely based on extrapolation from epidemiologic studies that were conducted in past decades.4-8 A single randomized controlled trial found that penicillin and clindamycin, antimicrobials with similar antimicrobial activity against anaerobes, to be equally effective.9 However, the recent literature emphasizes the polymicrobial nature of aspiration pneumonia in adults, with the common isolation of Gram-negative enteric bacteria.10 Further, while Pseudomonas aeruginosa is often identified in respiratory cultures from children with NI and chronic respiratory insufficiency,11,12 the significance of P. aeruginosa in lower airways remains unclear.

We designed this study to compare hospital outcomes associated with the most commonly prescribed empiric antimicrobial therapies for aspiration pneumonia in children with NI.

MATERIALS AND METHODS

Study Design and Data Source

This multicenter, retrospective cohort study used the Pediatric Health Information System (PHIS) database. PHIS, an administrative database of 50 not-for-profit tertiary care pediatric hospitals, contains data regarding patient demographics, diagnoses and procedures, and daily billed resource utilization, including laboratory and imaging studies. Data quality and reliability are assured through the Children’s Hospital Association (CHA; Lenexa, Kansas) and participating hospitals. Due to incomplete data through the study period and data quality issues, six hospitals were excluded.

STUDY POPULATION

Inclusion Criteria

Children 1-18 years of age who were discharged between July 1, 2007 and June 30, 2015 were included if they had a NI diagnosis,1 a principal diagnosis indicative of aspiration pneumonia (507.x),3,13,14 and received antibiotics in the first two calendar days of admission. NI was determined using previously defined International Classification of Diseases, Ninth Revision-Clinical Modification (ICD-9-CM) diagnosis codes.1 We only included children who received antibiotics in the first two calendar days of admission to minimize the likelihood of including children admitted for other reasons who acquired aspiration pneumonia after hospitalization. For children with multiple hospitalizations, one admission was randomly selected for inclusion to minimize weighting results toward repeat visits.

 

 

Exclusion Criteria

Children transferred from another hospital were excluded as records from their initial presentation, including treatment and outcomes, were not available. We also excluded children with tracheostomy15,16 or chronic ventilator dependence,17 those with a diagnosis of human immunodeficiency virus or tuberculosis, and children who received chemotherapy during hospitalization given expected differences in etiology, treatment, and outcomes.18

Exposure

The primary exposure was antibiotic therapy received in the first two days of admission. Antibiotics were classified by their antimicrobial spectra of activity as defined by The Sanford Guide to Antimicrobial Therapy19 against the most commonly recognized pathogens of aspiration pneumonia: anaerobes, Gram-negatives, and P. aeruginosa (Appendix Table 1).10,20 For example, penicillin G and clindamycin were among the antibiotics classified as providing anaerobic coverage alone, whereas ceftriaxone was classified as providing Gram-negative coverage alone and ampicillin-sulbactam or as combination therapy with clindamycin and ceftriaxone were classified as providing anaerobic and Gram-negative coverage. Piperacillin-tazobactam and meropenem were classified as providing anaerobic, Gram-negative, and P. aeruginosa coverage. We excluded antibiotics that do not provide coverage against anaerobes, Gram-negative, or P. aeruginosa (eg, ampicillin, azithromycin) or that provide coverage against Gram-negative and P. aeruginosa, but not anaerobes (eg, cefepime, tobramycin), as these therapies were prescribed for <5% of the cohort. We chose not to examine the coverage for Streptococcus pneumonia or Staphylococcus aureus as antibiotics included in this analysis covered these bacteria for 99.9% of our cohort.

OUTCOMES

Outcomes included acute respiratory failure during hospitalization, intensive care unit (ICU) transfer, and hospital length of stay (LOS). Acute respiratory failure during hospitalization was defined as the presence of Clinical Transaction Classification (CTC) or ICD-9 procedure code for noninvasive or invasive mechanical ventilation on day two or later of hospitalization, with or without the need for respiratory support on day 0 or day 1 (Appendix Table 2). Given the variability in hospital policies that may drive ICU admission criteria for complex patients, our outcome of ICU transfer was defined as the requirement for ICU level care on day two or later of hospitalization without ICU admission. Acute respiratory failure and ICU care occurring within the first two hospital days were not classified as outcomes because these early events likely reflect illness severity at presentation rather than outcomes attributable to treatment failure; these were included as markers of severity in the models.

Patient Demographics and Clinical Characteristics

Demographic and clinical characteristics that might influence antibiotic choice and/or hospital outcomes were assessed. Clinical characteristics included complex chronic conditions,21-23 medical technology assistance,24 performance of diagnostic testing, and markers of severe illness on presentation. Diagnostic testing included bacterial cultures (blood, respiratory, urine) and chest radiograph performance in the first two days of hospitalization. Results of diagnostic testing are not available in the PHIS. Illness severity on presentation included acute respiratory failure, pleural drainage, receipt of vasoactive agents, and transfusion of blood products in the first two days of hospitalization (Appendix Table 2).17,25,26

STASTICAL ANALYSIS

Continuous data were described with median and interquartile ranges (IQR) due to nonnormal distribution. Categorical data were described with frequencies and percentages. Patient demographics, clinical characteristics, and hospital outcomes were stratified by empiric antimicrobial coverage and compared using chi-square and Kruskal–Wallis tests as appropriate.

 

 

Generalized linear mixed-effects models with random hospital intercepts were derived to assess the independent effect of antimicrobial spectra of activity on outcomes of acute respiratory failure, ICU transfer, and LOS while adjusting for important differences in demographic and clinical characteristics. LOS had a nonnormal distribution. Thus, we used an exponential distribution. Covariates were chosen a priori given the clinical and biological relevance to exposure and outcomes—age, presence of complex chronic condition diagnoses, the number of complex chronic conditions, technology dependence, the performance of diagnostic tests on presentation, and illness severity on presentation. ICU admission was included as a covariate in acute respiratory failure and LOS outcome models. The results of the model for acute respiratory failure and ICU transfer are presented as adjusted odds ratios (OR) with a 95% CI. LOS results are presented as adjusted rate ratios (RR) with 95% CI.

All analyses were performed with SAS 9.3 (SAS Institute, Cary, North Carolina). P values <.05 were considered statistically significant. Cincinnati Children’s Hospital Medical Center Institutional Review Board considered this deidentified dataset study as not human subjects research.

RESULTS

Study Cohort

At the 44 hospitals included, 4,812 children with NI hospitalized with the diagnosis of aspiration pneumonia met the eligibility criteria. However, 79 received antibiotics with the spectra of activity not examined, leaving 4,733 children in our final analysis (Appendix Figure). Demographic and clinical characteristics of the study cohort are shown in Table 1. Median age was five years (interquartile range [IQR]: 2-11 years). Most subjects were male (53.9%), non-Hispanic white (47.9%), and publicly insured (63.6%). There was a slight variation in the distribution of admissions across seasons (spring 31.6%, summer 19.2%, fall 21.3%, and winter 27.9%). One-third of children had four or more comorbid CCCs (complex chronic conditions; 34.2%). The three most common nonneurologic CCC diagnosis categories were gastrointestinal (63.1%), congenital and/or genetic defects (36.9%), and respiratory (8.9%). Assistance with medical technologies was also common (82%)—particularly gastrointestinal (63.1%) and neurologic/neuromuscular (9.8%) technologies. The vast majority of children (92.5%) had either a chest radiograph (90.5%), respiratory viral study (33.7%), or respiratory culture (10.0%) obtained on presentation. A minority required noninvasive or invasive respiratory support (25.4%), vasoactive agents (8.9%), blood products (1.2%), or pleural drainage (0.3%) in the first two hospital days.

Spectrum of Antimicrobial Coverage

Most children (57.9%) received anaerobic and Gram-negative coverage; 16.2% received anaerobic, Gram-negative and P. aeruginosa coverage; 15.3% received anaerobic coverage alone; and 10.6% received Gram-negative coverage alone. Empiric antimicrobial coverage varied substantially across hospitals: anaerobic coverage was prescribed for 0%-44% of patients; Gram-negative coverage was prescribed for 3%-26% of patients; anaerobic and Gram-negative coverage was prescribed for 25%-90% of patients; and anaerobic, Gram-negative, and P. aeruginosa coverage was prescribed for 0%-65% of patients (Figure 1).

There were several important differences between treatment groups (Table 1). Children receiving anaerobic, Gram-negative, and P. aeruginosa coverage were older, more likely to have certain CCCs (respiratory, gastrointestinal, and malignancy), have ≥4 CCCs, and require assistance with medical technologies (respiratory, gastrointestinal) compared with all other treatment groups. They were also more likely to have respiratory viral testing and bacterial cultures obtained and to have markers of severe illness on presentation.

 

 

Outcomes

Acute Respiratory Failure

One-quarter (25.4%) of patients had acute respiratory failure on presentation; 22.5% required respiratory support (continued from presentation or were new) on day two or later of hospitalization (Table 2). In the adjusted analysis, children receiving Gram-negative coverage alone had two-fold greater odds (OR 2.15, 95% CI: 1.41-3.27) and children receiving anaerobic and Gram-negative coverage had 1.6-fold greater odds (OR 1.65, 95% CI: 1.19-2.28), of respiratory failure during hospitalization compared with those receiving anaerobic coverage alone (Figure 2). Odds of respiratory failure during hospitalization did not significantly differ for children receiving anaerobic, Gram-negative, and P. aeruginosa coverage compared with those receiving anaerobic coverage alone.

ICU Transfer

Nearly thirty percent (29.0%) of children required ICU admission, with an additional 3.8% requiring ICU transfer following admission (Table 2). In the multivariable analysis, the odds of an ICU transfer were greater for children receiving Gram-negative coverage alone (OR 1.80, 95% CI: 1.03-3.14) compared with those receiving anaerobic coverage alone. There was no statistical difference in ICU transfer for those receiving anaerobic and Gram-negative coverage (with or without P. aeruginosa coverage) compared with those receiving anaerobic coverage alone (Figure 2).

Length of Stay

Median hospital LOS for the total cohort was five days (IQR: 3-9 days; Table 2). In the multivariable analysis, children receiving Gram-negative coverage alone had a longer LOS (RR 1.28; 95% CI: 1.16-1.41) compared with those receiving anaerobic coverage alone, whereas children receiving anaerobic, Gram-negative, and P. aeruginosa coverage had a shorter LOS (RR 0.83; 95% CI: 0.76-0.90) than those receiving anaerobic coverage alone (Figure 2). There was no statistical difference in the LOS between children receiving anaerobic and Gram-negative coverage and those receiving anaerobic coverage alone.

DISCUSSION

In this multicenter study of children with NI hospitalized with aspiration pneumonia, we found substantial variation in empiric antimicrobial coverage for children with aspiration pneumonia. When comparing outcomes across groups, children who received anaerobic and Gram-negative coverage had outcomes similar to children who received anaerobic therapy alone. However, children who did not receive anaerobic coverage (ie, Gram-negative coverage alone) had worse outcomes, most notably a greater than two-fold increase in the odds of experiencing acute respiratory failure during hospitalization when compared with children receiving anaerobic therapy. These findings support prior literature that has highlighted the importance of anaerobic therapy in the treatment of aspiration pneumonia. The benefit of antibiotics targeting Gram-negative organisms, in addition to anaerobes, remains uncertain.

The variability in empiric antimicrobial coverage likely reflects the paucity of available information on oral and/or enteric bacteria required to identify them as causative organisms in aspiration pneumonia. In part, this problem is due to the difficulty in obtaining adequate sputum for culture from pediatric patients.27 While it may be more feasible to obtain tracheal aspirates for respiratory culture in children with a tracheostomy, interpretation of culture results remains challenging because the lower airways of children with tracheostomy are commonly colonized with bacterial pathogens.28 Thus, physicians are often left to choose empiric antimicrobial coverage with inadequate supporting evidence.29 Although the polymicrobial nature of aspiration pneumonia is well recognized in adult and pediatric literature,10,30 it is less clear which organisms are of pathological significance and require treatment.

The treatment standard for aspiration pneumonia has long included anaerobic therapy.29 The worse outcomes of children not receiving anaerobic therapy (ie, Gram-negative coverage alone) compared with children who received anaerobic therapy support the continued importance of anaerobic therapy in the treatment of aspiration pneumonia for hospitalized children with NI. The role of antibiotics covering Gram-negative organisms is less clear. Recent studies suggest the role of anaerobes is overemphasized in the etiology and treatment of aspiration pneumonia.10,29,31-38 Multiple studies on aspiration pneumonia bacteriology in hospitalized adults have demonstrated a predominance of Gram-negative organisms (ranging from 37%-71% of isolates identified on respiratory culture) and a relative scarcity of anaerobes (ranging from 0%-16% of isolates).31-37 A prospective study of 50 children hospitalized with clinical and radiographic evidence of pneumonia with known aspiration risk (eg, neuromuscular disease or dysphagia) found that ~80% of 163 bacterial isolates were Gram-negative.38 However, this study included repeat cultures from the same children, and thus, may overestimate the prevalence of Gram-negative organisms. In our study, children who received both anaerobic and Gram-negative therapy had no differences in ICU transfer or LOS but did experience higher odds of acute respiratory failure. As these results may be due to unmeasured confounding, future studies should further explore the necessity of Gram-negative coverage in addition to anaerobic coverage in this population.

While these recent studies may seem to suggest that anaerobic coverage is not necessary for aspiration pneumonia, there are important limitations worth noting. First, these studies used a variety of sampling techniques. While organisms grown from samples obtained via bronchoalveolar lavage31-34,36 are likely pathogenic, those grown from tracheal or oral samples obtained via percutaneous transtracheal aspiration,34 a protected specimen brush,34,36,37 or expectorated sputum35,38 may not represent lower airway organisms. Second, anaerobic cultures were not obtained in all studies.31,34,38 Anaerobic organisms are difficult to isolate using traditional clinical specimen collection techniques and aerobic culture media.18 Furthermore, anaerobes are not easily recovered from lung infections after the receipt of antibiotic therapy.39 Details regarding pretreatment, which are largely lacking from these studies, are necessary to interpret the relative scarcity of anaerobes on respiratory culture. Finally, caution should be taken when extrapolating the results of studies focused on the etiology and treatment of aspiration pneumonia in elderly adults to children. Our results, particularly in the context of the limitation of these more recent studies, suggest that the role of anaerobes has been underestimated.

Recent studies examining populations of children with cerebral palsy and/or tracheostomy have emphasized the high rates of carriage and infection rates with Gram-negative and drug-resistant bacteria; in particular, P. aeruginosa accounts for 50%-72% of pathogenic bacteria.11,12,38,40These studies note the generally poor outcomes of children with P. aeruginosa—including multiple and longer hospitalizations, frequent readmissions, and the increased severity of pneumonia, including the need for ICU admission, pleural effusions, the need for intubation, and mortality.11,12,38,40,41 In our study, nearly 35% of children who received anaerobic, Gram-negative, and P. aeruginosa coverage experienced acute respiratory failure during hospitalization compared with 20% of children who received other therapies. While these results might seem to suggest that broader spectrum therapy is harmful, they must be interpreted in the context of important population differences; children who received a combination of anaerobic, Gram-negative, and P. aeruginosa coverage had greater medical complexity and greater severity of illness on presentation. Such factors may provide the reason for the appropriate prescription of antipseudomonal antibiotics (eg, history of tracheostomy colonization or infection, long-term care facility resident).42 When we controlled for population differences, children who received antipseudomonal therapy had a significantly shorter LOS and no differences in outcomes of acute respiratory failure or ICU transfer compared with those receiving anaerobic therapy alone. This result suggests that worse outcomes were associated with antipseudomonal therapy on unadjusted analyses resulting from underlying medical complexity and illness severity rather than from colonization or infection with P. aeruginosa.

Our multicenter observational study has several limitations. We used diagnosis codes to identify patients with aspiration pneumonia. As validated clinical criteria for the diagnosis of aspiration pneumonia do not exist, clinicians may assign a diagnosis of and treatment for aspiration pneumonia by subjective suspicion based on a child’s severe NI or illness severity on presentation leading to selection bias. Although administrative data are not able to verify pneumonia type with absolute certainty, we previously demonstrated that the differences in the outcomes of children with aspiration and nonaspiration pneumonia diagnosis codes persist after accounting for the complexity that might influence the diagnosis.3It is also possible that the diagnosis of aspiration pneumonia was not made upon admission for a subset of patients leading to misclassification of exposure. Some children may have had aspiration pneumonia on admission but were not assigned that diagnosis or treated for presumed aspiration pneumonia until later in the hospital course as they demonstrated treatment failure or clinical worsening. It is also possible that some children had an aspiration event during hospitalization that developed into aspiration pneumonia. We attempted to adjust for medical complexity and illness severity through multivariable adjustment based on the diagnosis and procedure codes, as well as the laboratory testing performed. However, unmeasured or residual confounding may remain as administrative data are not equipped to distinguish detailed functional status (eg, ability to cough, chest wall strength) or illness severity (eg, respiratory distress) that might influence antibiotic selection and/or outcomes.

Frthermore, we were unable to account for laboratory, microbiology, or radiology test results, and other management practices (eg, frequency of airway clearance, previous antimicrobial therapy) that may influence outcomes. Future studies should certainly include an examination of the concordance of the antibiotics prescribed with causative organisms, as this undoubtedly affects patient outcomes. Other outcomes are important to examine (eg, time to return to respiratory baseline), but we were unable to do so, given the lack of clinical detail in our database. We randomly selected a single hospitalization for children with multiple admissions; alternative methods could have different results. Although children with NI predominately use children’s hospitals,1 results may not be generalizable.

 

 

CONCLUSION

These findings support prior literature that has highlighted the important role anaerobic therapy plays in the treatment of aspiration pneumonia in children with NI. In light of the limitations of our study design, we believe that rigorous clinical trials comparing anaerobic with anaerobic and Gram-negative therapy are an important and necessary next step to determine the optimal treatment for aspiration pneumonia in this population.

Disclosures

The authors do not have any financial relationships relevant to this article to disclose.

Funding

Dr. Thomson was supported by the Agency for Healthcare Research and Quality (AHRQ) under award number K08HS025138. Dr. Ambroggio was supported by the National Institute for Allergy and Infectious Diseases (NIAID) under award number K01AI125413. The content is solely the responsibility of the authors and does not necessarily represent the official views of the AHRQ or NIAID.

Neurologic impairment (NI) encompasses static and progressive diseases of the central and/or peripheral nervous systems that result in functional and intellectual impairments.1 While a variety of neurologic diseases are responsible for NI (eg, hypoxic-ischemic encephalopathy, muscular dystrophy), consequences of these diseases extend beyond neurologic manifestations.1 These children are at an increased risk for aspiration of oral and gastric contents given their common comorbidities of dysphagia, gastroesophageal reflux, impaired cough, and respiratory muscle weakness.2 While aspiration may manifest as a self-resolving pneumonitis, the presence of oral or enteric bacteria in aspirated material may result in the development of bacterial pneumonia. Children with NI hospitalized with aspiration pneumonia have higher complication rates, longer and costlier hospitalizations, and higher readmission rates when compared with children with nonaspiration pneumonia.3

While pediatric aspiration pneumonia is commonly attributed to anaerobic bacteria, this is largely based on extrapolation from epidemiologic studies that were conducted in past decades.4-8 A single randomized controlled trial found that penicillin and clindamycin, antimicrobials with similar antimicrobial activity against anaerobes, to be equally effective.9 However, the recent literature emphasizes the polymicrobial nature of aspiration pneumonia in adults, with the common isolation of Gram-negative enteric bacteria.10 Further, while Pseudomonas aeruginosa is often identified in respiratory cultures from children with NI and chronic respiratory insufficiency,11,12 the significance of P. aeruginosa in lower airways remains unclear.

We designed this study to compare hospital outcomes associated with the most commonly prescribed empiric antimicrobial therapies for aspiration pneumonia in children with NI.

MATERIALS AND METHODS

Study Design and Data Source

This multicenter, retrospective cohort study used the Pediatric Health Information System (PHIS) database. PHIS, an administrative database of 50 not-for-profit tertiary care pediatric hospitals, contains data regarding patient demographics, diagnoses and procedures, and daily billed resource utilization, including laboratory and imaging studies. Data quality and reliability are assured through the Children’s Hospital Association (CHA; Lenexa, Kansas) and participating hospitals. Due to incomplete data through the study period and data quality issues, six hospitals were excluded.

STUDY POPULATION

Inclusion Criteria

Children 1-18 years of age who were discharged between July 1, 2007 and June 30, 2015 were included if they had a NI diagnosis,1 a principal diagnosis indicative of aspiration pneumonia (507.x),3,13,14 and received antibiotics in the first two calendar days of admission. NI was determined using previously defined International Classification of Diseases, Ninth Revision-Clinical Modification (ICD-9-CM) diagnosis codes.1 We only included children who received antibiotics in the first two calendar days of admission to minimize the likelihood of including children admitted for other reasons who acquired aspiration pneumonia after hospitalization. For children with multiple hospitalizations, one admission was randomly selected for inclusion to minimize weighting results toward repeat visits.

 

 

Exclusion Criteria

Children transferred from another hospital were excluded as records from their initial presentation, including treatment and outcomes, were not available. We also excluded children with tracheostomy15,16 or chronic ventilator dependence,17 those with a diagnosis of human immunodeficiency virus or tuberculosis, and children who received chemotherapy during hospitalization given expected differences in etiology, treatment, and outcomes.18

Exposure

The primary exposure was antibiotic therapy received in the first two days of admission. Antibiotics were classified by their antimicrobial spectra of activity as defined by The Sanford Guide to Antimicrobial Therapy19 against the most commonly recognized pathogens of aspiration pneumonia: anaerobes, Gram-negatives, and P. aeruginosa (Appendix Table 1).10,20 For example, penicillin G and clindamycin were among the antibiotics classified as providing anaerobic coverage alone, whereas ceftriaxone was classified as providing Gram-negative coverage alone and ampicillin-sulbactam or as combination therapy with clindamycin and ceftriaxone were classified as providing anaerobic and Gram-negative coverage. Piperacillin-tazobactam and meropenem were classified as providing anaerobic, Gram-negative, and P. aeruginosa coverage. We excluded antibiotics that do not provide coverage against anaerobes, Gram-negative, or P. aeruginosa (eg, ampicillin, azithromycin) or that provide coverage against Gram-negative and P. aeruginosa, but not anaerobes (eg, cefepime, tobramycin), as these therapies were prescribed for <5% of the cohort. We chose not to examine the coverage for Streptococcus pneumonia or Staphylococcus aureus as antibiotics included in this analysis covered these bacteria for 99.9% of our cohort.

OUTCOMES

Outcomes included acute respiratory failure during hospitalization, intensive care unit (ICU) transfer, and hospital length of stay (LOS). Acute respiratory failure during hospitalization was defined as the presence of Clinical Transaction Classification (CTC) or ICD-9 procedure code for noninvasive or invasive mechanical ventilation on day two or later of hospitalization, with or without the need for respiratory support on day 0 or day 1 (Appendix Table 2). Given the variability in hospital policies that may drive ICU admission criteria for complex patients, our outcome of ICU transfer was defined as the requirement for ICU level care on day two or later of hospitalization without ICU admission. Acute respiratory failure and ICU care occurring within the first two hospital days were not classified as outcomes because these early events likely reflect illness severity at presentation rather than outcomes attributable to treatment failure; these were included as markers of severity in the models.

Patient Demographics and Clinical Characteristics

Demographic and clinical characteristics that might influence antibiotic choice and/or hospital outcomes were assessed. Clinical characteristics included complex chronic conditions,21-23 medical technology assistance,24 performance of diagnostic testing, and markers of severe illness on presentation. Diagnostic testing included bacterial cultures (blood, respiratory, urine) and chest radiograph performance in the first two days of hospitalization. Results of diagnostic testing are not available in the PHIS. Illness severity on presentation included acute respiratory failure, pleural drainage, receipt of vasoactive agents, and transfusion of blood products in the first two days of hospitalization (Appendix Table 2).17,25,26

STASTICAL ANALYSIS

Continuous data were described with median and interquartile ranges (IQR) due to nonnormal distribution. Categorical data were described with frequencies and percentages. Patient demographics, clinical characteristics, and hospital outcomes were stratified by empiric antimicrobial coverage and compared using chi-square and Kruskal–Wallis tests as appropriate.

 

 

Generalized linear mixed-effects models with random hospital intercepts were derived to assess the independent effect of antimicrobial spectra of activity on outcomes of acute respiratory failure, ICU transfer, and LOS while adjusting for important differences in demographic and clinical characteristics. LOS had a nonnormal distribution. Thus, we used an exponential distribution. Covariates were chosen a priori given the clinical and biological relevance to exposure and outcomes—age, presence of complex chronic condition diagnoses, the number of complex chronic conditions, technology dependence, the performance of diagnostic tests on presentation, and illness severity on presentation. ICU admission was included as a covariate in acute respiratory failure and LOS outcome models. The results of the model for acute respiratory failure and ICU transfer are presented as adjusted odds ratios (OR) with a 95% CI. LOS results are presented as adjusted rate ratios (RR) with 95% CI.

All analyses were performed with SAS 9.3 (SAS Institute, Cary, North Carolina). P values <.05 were considered statistically significant. Cincinnati Children’s Hospital Medical Center Institutional Review Board considered this deidentified dataset study as not human subjects research.

RESULTS

Study Cohort

At the 44 hospitals included, 4,812 children with NI hospitalized with the diagnosis of aspiration pneumonia met the eligibility criteria. However, 79 received antibiotics with the spectra of activity not examined, leaving 4,733 children in our final analysis (Appendix Figure). Demographic and clinical characteristics of the study cohort are shown in Table 1. Median age was five years (interquartile range [IQR]: 2-11 years). Most subjects were male (53.9%), non-Hispanic white (47.9%), and publicly insured (63.6%). There was a slight variation in the distribution of admissions across seasons (spring 31.6%, summer 19.2%, fall 21.3%, and winter 27.9%). One-third of children had four or more comorbid CCCs (complex chronic conditions; 34.2%). The three most common nonneurologic CCC diagnosis categories were gastrointestinal (63.1%), congenital and/or genetic defects (36.9%), and respiratory (8.9%). Assistance with medical technologies was also common (82%)—particularly gastrointestinal (63.1%) and neurologic/neuromuscular (9.8%) technologies. The vast majority of children (92.5%) had either a chest radiograph (90.5%), respiratory viral study (33.7%), or respiratory culture (10.0%) obtained on presentation. A minority required noninvasive or invasive respiratory support (25.4%), vasoactive agents (8.9%), blood products (1.2%), or pleural drainage (0.3%) in the first two hospital days.

Spectrum of Antimicrobial Coverage

Most children (57.9%) received anaerobic and Gram-negative coverage; 16.2% received anaerobic, Gram-negative and P. aeruginosa coverage; 15.3% received anaerobic coverage alone; and 10.6% received Gram-negative coverage alone. Empiric antimicrobial coverage varied substantially across hospitals: anaerobic coverage was prescribed for 0%-44% of patients; Gram-negative coverage was prescribed for 3%-26% of patients; anaerobic and Gram-negative coverage was prescribed for 25%-90% of patients; and anaerobic, Gram-negative, and P. aeruginosa coverage was prescribed for 0%-65% of patients (Figure 1).

There were several important differences between treatment groups (Table 1). Children receiving anaerobic, Gram-negative, and P. aeruginosa coverage were older, more likely to have certain CCCs (respiratory, gastrointestinal, and malignancy), have ≥4 CCCs, and require assistance with medical technologies (respiratory, gastrointestinal) compared with all other treatment groups. They were also more likely to have respiratory viral testing and bacterial cultures obtained and to have markers of severe illness on presentation.

 

 

Outcomes

Acute Respiratory Failure

One-quarter (25.4%) of patients had acute respiratory failure on presentation; 22.5% required respiratory support (continued from presentation or were new) on day two or later of hospitalization (Table 2). In the adjusted analysis, children receiving Gram-negative coverage alone had two-fold greater odds (OR 2.15, 95% CI: 1.41-3.27) and children receiving anaerobic and Gram-negative coverage had 1.6-fold greater odds (OR 1.65, 95% CI: 1.19-2.28), of respiratory failure during hospitalization compared with those receiving anaerobic coverage alone (Figure 2). Odds of respiratory failure during hospitalization did not significantly differ for children receiving anaerobic, Gram-negative, and P. aeruginosa coverage compared with those receiving anaerobic coverage alone.

ICU Transfer

Nearly thirty percent (29.0%) of children required ICU admission, with an additional 3.8% requiring ICU transfer following admission (Table 2). In the multivariable analysis, the odds of an ICU transfer were greater for children receiving Gram-negative coverage alone (OR 1.80, 95% CI: 1.03-3.14) compared with those receiving anaerobic coverage alone. There was no statistical difference in ICU transfer for those receiving anaerobic and Gram-negative coverage (with or without P. aeruginosa coverage) compared with those receiving anaerobic coverage alone (Figure 2).

Length of Stay

Median hospital LOS for the total cohort was five days (IQR: 3-9 days; Table 2). In the multivariable analysis, children receiving Gram-negative coverage alone had a longer LOS (RR 1.28; 95% CI: 1.16-1.41) compared with those receiving anaerobic coverage alone, whereas children receiving anaerobic, Gram-negative, and P. aeruginosa coverage had a shorter LOS (RR 0.83; 95% CI: 0.76-0.90) than those receiving anaerobic coverage alone (Figure 2). There was no statistical difference in the LOS between children receiving anaerobic and Gram-negative coverage and those receiving anaerobic coverage alone.

DISCUSSION

In this multicenter study of children with NI hospitalized with aspiration pneumonia, we found substantial variation in empiric antimicrobial coverage for children with aspiration pneumonia. When comparing outcomes across groups, children who received anaerobic and Gram-negative coverage had outcomes similar to children who received anaerobic therapy alone. However, children who did not receive anaerobic coverage (ie, Gram-negative coverage alone) had worse outcomes, most notably a greater than two-fold increase in the odds of experiencing acute respiratory failure during hospitalization when compared with children receiving anaerobic therapy. These findings support prior literature that has highlighted the importance of anaerobic therapy in the treatment of aspiration pneumonia. The benefit of antibiotics targeting Gram-negative organisms, in addition to anaerobes, remains uncertain.

The variability in empiric antimicrobial coverage likely reflects the paucity of available information on oral and/or enteric bacteria required to identify them as causative organisms in aspiration pneumonia. In part, this problem is due to the difficulty in obtaining adequate sputum for culture from pediatric patients.27 While it may be more feasible to obtain tracheal aspirates for respiratory culture in children with a tracheostomy, interpretation of culture results remains challenging because the lower airways of children with tracheostomy are commonly colonized with bacterial pathogens.28 Thus, physicians are often left to choose empiric antimicrobial coverage with inadequate supporting evidence.29 Although the polymicrobial nature of aspiration pneumonia is well recognized in adult and pediatric literature,10,30 it is less clear which organisms are of pathological significance and require treatment.

The treatment standard for aspiration pneumonia has long included anaerobic therapy.29 The worse outcomes of children not receiving anaerobic therapy (ie, Gram-negative coverage alone) compared with children who received anaerobic therapy support the continued importance of anaerobic therapy in the treatment of aspiration pneumonia for hospitalized children with NI. The role of antibiotics covering Gram-negative organisms is less clear. Recent studies suggest the role of anaerobes is overemphasized in the etiology and treatment of aspiration pneumonia.10,29,31-38 Multiple studies on aspiration pneumonia bacteriology in hospitalized adults have demonstrated a predominance of Gram-negative organisms (ranging from 37%-71% of isolates identified on respiratory culture) and a relative scarcity of anaerobes (ranging from 0%-16% of isolates).31-37 A prospective study of 50 children hospitalized with clinical and radiographic evidence of pneumonia with known aspiration risk (eg, neuromuscular disease or dysphagia) found that ~80% of 163 bacterial isolates were Gram-negative.38 However, this study included repeat cultures from the same children, and thus, may overestimate the prevalence of Gram-negative organisms. In our study, children who received both anaerobic and Gram-negative therapy had no differences in ICU transfer or LOS but did experience higher odds of acute respiratory failure. As these results may be due to unmeasured confounding, future studies should further explore the necessity of Gram-negative coverage in addition to anaerobic coverage in this population.

While these recent studies may seem to suggest that anaerobic coverage is not necessary for aspiration pneumonia, there are important limitations worth noting. First, these studies used a variety of sampling techniques. While organisms grown from samples obtained via bronchoalveolar lavage31-34,36 are likely pathogenic, those grown from tracheal or oral samples obtained via percutaneous transtracheal aspiration,34 a protected specimen brush,34,36,37 or expectorated sputum35,38 may not represent lower airway organisms. Second, anaerobic cultures were not obtained in all studies.31,34,38 Anaerobic organisms are difficult to isolate using traditional clinical specimen collection techniques and aerobic culture media.18 Furthermore, anaerobes are not easily recovered from lung infections after the receipt of antibiotic therapy.39 Details regarding pretreatment, which are largely lacking from these studies, are necessary to interpret the relative scarcity of anaerobes on respiratory culture. Finally, caution should be taken when extrapolating the results of studies focused on the etiology and treatment of aspiration pneumonia in elderly adults to children. Our results, particularly in the context of the limitation of these more recent studies, suggest that the role of anaerobes has been underestimated.

Recent studies examining populations of children with cerebral palsy and/or tracheostomy have emphasized the high rates of carriage and infection rates with Gram-negative and drug-resistant bacteria; in particular, P. aeruginosa accounts for 50%-72% of pathogenic bacteria.11,12,38,40These studies note the generally poor outcomes of children with P. aeruginosa—including multiple and longer hospitalizations, frequent readmissions, and the increased severity of pneumonia, including the need for ICU admission, pleural effusions, the need for intubation, and mortality.11,12,38,40,41 In our study, nearly 35% of children who received anaerobic, Gram-negative, and P. aeruginosa coverage experienced acute respiratory failure during hospitalization compared with 20% of children who received other therapies. While these results might seem to suggest that broader spectrum therapy is harmful, they must be interpreted in the context of important population differences; children who received a combination of anaerobic, Gram-negative, and P. aeruginosa coverage had greater medical complexity and greater severity of illness on presentation. Such factors may provide the reason for the appropriate prescription of antipseudomonal antibiotics (eg, history of tracheostomy colonization or infection, long-term care facility resident).42 When we controlled for population differences, children who received antipseudomonal therapy had a significantly shorter LOS and no differences in outcomes of acute respiratory failure or ICU transfer compared with those receiving anaerobic therapy alone. This result suggests that worse outcomes were associated with antipseudomonal therapy on unadjusted analyses resulting from underlying medical complexity and illness severity rather than from colonization or infection with P. aeruginosa.

Our multicenter observational study has several limitations. We used diagnosis codes to identify patients with aspiration pneumonia. As validated clinical criteria for the diagnosis of aspiration pneumonia do not exist, clinicians may assign a diagnosis of and treatment for aspiration pneumonia by subjective suspicion based on a child’s severe NI or illness severity on presentation leading to selection bias. Although administrative data are not able to verify pneumonia type with absolute certainty, we previously demonstrated that the differences in the outcomes of children with aspiration and nonaspiration pneumonia diagnosis codes persist after accounting for the complexity that might influence the diagnosis.3It is also possible that the diagnosis of aspiration pneumonia was not made upon admission for a subset of patients leading to misclassification of exposure. Some children may have had aspiration pneumonia on admission but were not assigned that diagnosis or treated for presumed aspiration pneumonia until later in the hospital course as they demonstrated treatment failure or clinical worsening. It is also possible that some children had an aspiration event during hospitalization that developed into aspiration pneumonia. We attempted to adjust for medical complexity and illness severity through multivariable adjustment based on the diagnosis and procedure codes, as well as the laboratory testing performed. However, unmeasured or residual confounding may remain as administrative data are not equipped to distinguish detailed functional status (eg, ability to cough, chest wall strength) or illness severity (eg, respiratory distress) that might influence antibiotic selection and/or outcomes.

Frthermore, we were unable to account for laboratory, microbiology, or radiology test results, and other management practices (eg, frequency of airway clearance, previous antimicrobial therapy) that may influence outcomes. Future studies should certainly include an examination of the concordance of the antibiotics prescribed with causative organisms, as this undoubtedly affects patient outcomes. Other outcomes are important to examine (eg, time to return to respiratory baseline), but we were unable to do so, given the lack of clinical detail in our database. We randomly selected a single hospitalization for children with multiple admissions; alternative methods could have different results. Although children with NI predominately use children’s hospitals,1 results may not be generalizable.

 

 

CONCLUSION

These findings support prior literature that has highlighted the important role anaerobic therapy plays in the treatment of aspiration pneumonia in children with NI. In light of the limitations of our study design, we believe that rigorous clinical trials comparing anaerobic with anaerobic and Gram-negative therapy are an important and necessary next step to determine the optimal treatment for aspiration pneumonia in this population.

Disclosures

The authors do not have any financial relationships relevant to this article to disclose.

Funding

Dr. Thomson was supported by the Agency for Healthcare Research and Quality (AHRQ) under award number K08HS025138. Dr. Ambroggio was supported by the National Institute for Allergy and Infectious Diseases (NIAID) under award number K01AI125413. The content is solely the responsibility of the authors and does not necessarily represent the official views of the AHRQ or NIAID.

References

1. Berry JG, Poduri A, Bonkowsky JL, et al. Trends in resource utilization by children with neurological impairment in the United States inpatient health care system: a repeat cross-sectional study. PLoS Med. 2012;9(1):e1001158. https://doi.org/10.1371/journal.pmed.1001158.
2. Seddon PC, Khan Y. Respiratory problems in children with neurological impairment. Arch Dis Child. 2003;88(1):75-78. https://doi.org/10.1136/adc.88.1.75.
3. Thomson J, Hall M, Ambroggio L, et al. Aspiration and non-aspiration pneumonia in hospitalized children with neurologic impairment. Pediatrics. 2016;137(2):e20151612. https://doi.org/10.1542/peds.2015-1612.
4. Brook I. Anaerobic pulmonary infections in children. Pediatr Emerg Care. 2004;20(9):636-640. https://doi.org/10.1097/01.pec.0000139751.63624.0b.
5. Bartlett JG, Gorbach SL. Treatment of aspiration pneumonia and primary lung abscess. Penicillin G vs clindamycin. JAMA. 1975;234(9):935-937. https://doi.org/10.1001/jamadermatol.2017.0297.
6. Bartlett JG, Gorbach SL, Finegold SM. The bacteriology of aspiration pneumonia. Am J Med. 1974;56(2):202-207. https://doi.org/10.1016/0002-9343(74)90598-1.
7. Lode H. Microbiological and clinical aspects of aspiration pneumonia. J Antimicrob Chemother. 1988;21:83-90. https://doi.org/10.1093/jac/21.suppl_c.83.
8. Brook I. Treatment of aspiration or tracheostomy-associated pneumonia in neurologically impaired children: effect of antimicrobials effective against anaerobic bacteria. Int J Pediatr Otorhinolaryngol. 1996;35(2):171-177. https://doi.org/10.1016/0165-5876(96)01332-8.
9. Jacobson SJ, Griffiths K, Diamond S, et al. A randomized controlled trial of penicillin vs clindamycin for the treatment of aspiration pneumonia in children. Arch Pediatr Adolesc Med. 1997;151(7):701-704. https://doi.org/10.1001/archpedi.1997.02170440063011.
10. DiBardino DM, Wunderink RG. Aspiration pneumonia: a review of modern trends. J Crit Care. 2015;30(1):40-48. https://doi.org/10.1016/j.jcrc.2014.07.011.
11. Gerdung CA, Tsang A, Yasseen AS, 3rd, Armstrong K, McMillan HJ, Kovesi T. Association between chronic aspiration and chronic airway infection with Pseudomonas aeruginosa and other Gram-negative bacteria in children with cerebral palsy. Lung. 2016;194(2):307-314. https://doi.org/10.1007/s00408-016-9856-5.
12. Thorburn K, Jardine M, Taylor N, Reilly N, Sarginson RE, van Saene HK. Antibiotic-resistant bacteria and infection in children with cerebral palsy requiring mechanical ventilation. Pedr Crit Care Med. 2009;10(2):222-226. https://doi.org/10.1097/PCC.0b013e31819368ac.
13. Lanspa MJ, Jones BE, Brown SM, Dean NC. Mortality, morbidity, and disease severity of patients with aspiration pneumonia. J Hosp Med. 2013;8(2):83-90. https://doi.org/10.1002/jhm.1996.
14. Lanspa MJ, Peyrani P, Wiemken T, Wilson EL, Ramirez JA, Dean NC. Characteristics associated with clinician diagnosis of aspiration pneumonia: a descriptive study of afflicted patients and their outcomes. J Hosp Med. 2015;10(2):90-96. https://doi.org/10.1002/jhm.2280.
15. Berry JG, Graham RJ, Roberson DW, et al. Patient characteristics associated with in-hospital mortality in children following tracheotomy. Arch Dis Child. 2010;95(9):703-710.
16. Berry JG, Graham DA, Graham RJ, et al. Predictors of clinical outcomes and hospital resource use of children after tracheotomy. Pediatrics. 2009;124(2):563-572. https://doi.org/10.1136/adc.2009.180836.
17. Balamuth F, Weiss SL, Hall M, et al. Identifying pediatric severe sepsis and septic shock: Accuracy of diagnosis codes. J Pediatr. 2015;167(6):1295-1300 e1294. https://doi.org/10.1016/j.jpeds.2015.09.027.
18. American Academy of Pediatrics., Pickering LK, American Academy of Pediatrics. Committee on Infectious Diseases. In: Red book : 2012 report of the Committee on Infectious Diseases. 29th ed. Elk Grove Village: American Academy of Pediatrics; 2012.
19. Gilbert DN. The Sanford Guide to Antimicrobial Therapy 2014. 44th ed. Sperryville: Antimicrobial Therapy, Inc; 2011.
20. Marik PE. Aspiration pneumonitis and aspiration pneumonia. N Engl J Med. 2001;344(9):665-671. https://doi.org/10.1056/NEJM200103013440908.
21. Feudtner C, Feinstein JA, Zhong W, Hall M, Dai D. Pediatric complex chronic conditions classification system version 2: updated for ICD-10 and complex medical technology dependence and transplantation. BMC Pediatrics. 2014;14:199. https://doi.org/10.1186/1471-2431-14-199.
22. Feudtner C, Hays RM, Haynes G, Geyer JR, Neff JM, Koepsell TD. Deaths attributed to pediatric complex chronic conditions: national trends and implications for supportive care services. Pediatrics. 2001;107(6):E99. https://doi.org/10.1542/peds.107.6.e99.
23. Feinstein JA, Russell S, DeWitt PE, Feudtner C, Dai D, Bennett TD. R package for pediatric complex chronic condition classification. JAMA Pediatr. 2018;172(6):596-598. https://doi.org/10.1001/jamapediatrics.2018.0256.
24. Berry JG, Hall DE, Kuo DZ, Cohen E, Agrawal R, Feudtner C, Hall M, Kueser J, Kaplan W, Neff J. Hospital utilization and characteristics of patients experiencing recurrent readmissions within children’s hospitals. JAMA. 2011;305(7):682-690. https://doi.org/10.1001/jama.2011.122.
25. Shah SS, Hall M, Newland JG, et al. Comparative effectiveness of pleural drainage procedures for the treatment of complicated pneumonia in childhood. J Hosp Med. 2011;6(5):256-263. https://doi.org/10.1002/jhm.872.
26. Child Health Corporation of America. CTC™ 2010 Code Structure: Module 5 Clinical Services. 2010 January 4; Available at https://sharepoint.chca.com/CHCAForums/PerformanceImprovement/PHIS/Reference Library/CTC Resources/Forms/AllItems.aspx Version: Modified.
27. Bradley JS, Byington CL, Shah SS, et al. The management of community-acquired pneumonia in infants and children older than 3 months of age: clinical practice guidelines by the Pediatric Infectious Diseases Society and the Infectious Diseases Society of America. Clin Infect Dis. 2011;53(7):e25-76. https://doi.org/10.1093/cid/cir531.
28. Brook I. Bacterial colonization, tracheobronchitis, and pneumonia following tracheostomy and long-term intubation in pediatric patients. Chest. 1979;76(4):420-424.
29. Waybright RA, Coolidge W, Johnson TJ. Treatment of clinical aspiration: a reappraisal. Am J Health Syst Pharm. 2013;70(15):1291-1300. https://doi.org/10.2146/ajhp120319.
30. Brook I, Finegold SM. Bacteriology of aspiration pneumonia in children. Pediatrics. 1980;65(6):1115-1120.
31. Wei C, Cheng Z, Zhang L, Yang J. Microbiology and prognostic factors of hospital- and community-acquired aspiration pneumonia in respiratory intensive care unit. Am J Infect Control. 2013;41(10):880-884. https://doi.org/10.1016/j.ajic.2013.01.007.
32. El-Solh AA, Pietrantoni C, Bhat A, et al. Microbiology of severe aspiration pneumonia in institutionalized elderly. Am J Respir Crit Care Med. 2003;167(12):1650-1654. https://doi.org/10.1164/rccm.200212-1543OC.
33. Tokuyasu H, Harada T, Watanabe E, et al. Effectiveness of meropenem for the treatment of aspiration pneumonia in elderly patients. Intern Med. 2009;48(3):129-135. https://doi.org/10.2169/internalmedicine.48.1308.
34. Ott SR, Allewelt M, Lorenz J, Reimnitz P, Lode H, German Lung Abscess Study Group. Moxifloxacin vs ampicillin/sulbactam in aspiration pneumonia and primary lung abscess. Infection. 2008;36(1):23-30. https://doi.org/10.1007/s15010-007-7043-6.
35. Kadowaki M, Demura Y, Mizuno S, et al. Reappraisal of clindamycin IV monotherapy for treatment of mild-to-moderate aspiration pneumonia in elderly patients. Chest. 2005;127(4):1276-1282. https://doi.org/10.1016/j.chest.2017.05.019.
36. Marik PE, Careau P. The role of anaerobes in patients with ventilator-associated pneumonia and aspiration pneumonia: a prospective study. Chest. 1999;115(1):178-183. https://doi.org/10.1378/chest.115.1.178.
37. Mier L, Dreyfuss D, Darchy B, et al. Is penicillin G an adequate initial treatment for aspiration pneumonia? A prospective evaluation using a protected specimen brush and quantitative cultures. Intensive Care Med. 1993;19(5):279-284. https://doi.org/10.1007/bf01690548.
38. Ashkenazi-Hoffnung L, Ari A, Bilavsky E, Scheuerman O, Amir J, Prais D. Pseudomonas aeruginosa identified as a key pathogen in hospitalised children with aspiration pneumonia and a high aspiration risk. Acta Paediatr. 2016;105(12):e588-e592. https://doi.org/10.1111/apa.13523.
39. Bartlett JG, Gorbach SL, Tally FP, Finegold SM. Bacteriology and treatment of primary lung abscess. Am Rev Respir Dis. 1974;109(5):510-518. https://doi.org/10.1164/arrd.1974.109.5.510.
40. Russell CJ, Simon TD, Mamey MR, Newth CJL, Neely MN. Pseudomonas aeruginosa and post-tracheotomy bacterial respiratory tract infection readmissions. Pediatr Pulmonol. 2017;52(9):1212-1218. https://doi.org/10.1002/ppul.23716.
41. Russell CJ, Mamey MR, Koh JY, Schrager SM, Neely MN, Wu S. Length of stay and hospital revisit after bacterial tracheostomy-associated respiratory tract infection hospitalizations. Hosp Pediatr. Hosp Pediatr. 2018;8(2):72-80. https://doi.org/10.1542/hpeds.2017-0106.
42. Russell CJ, Mack WJ, Schrager SM, Wu S. Care variations and outcomes for children hospitalized with bacterial tracheostomy-associated respiratory infections. Hosp Pediatr. 2017;7(1):16-23. https://doi.org/10.1542/hpeds.2016-0104.

References

1. Berry JG, Poduri A, Bonkowsky JL, et al. Trends in resource utilization by children with neurological impairment in the United States inpatient health care system: a repeat cross-sectional study. PLoS Med. 2012;9(1):e1001158. https://doi.org/10.1371/journal.pmed.1001158.
2. Seddon PC, Khan Y. Respiratory problems in children with neurological impairment. Arch Dis Child. 2003;88(1):75-78. https://doi.org/10.1136/adc.88.1.75.
3. Thomson J, Hall M, Ambroggio L, et al. Aspiration and non-aspiration pneumonia in hospitalized children with neurologic impairment. Pediatrics. 2016;137(2):e20151612. https://doi.org/10.1542/peds.2015-1612.
4. Brook I. Anaerobic pulmonary infections in children. Pediatr Emerg Care. 2004;20(9):636-640. https://doi.org/10.1097/01.pec.0000139751.63624.0b.
5. Bartlett JG, Gorbach SL. Treatment of aspiration pneumonia and primary lung abscess. Penicillin G vs clindamycin. JAMA. 1975;234(9):935-937. https://doi.org/10.1001/jamadermatol.2017.0297.
6. Bartlett JG, Gorbach SL, Finegold SM. The bacteriology of aspiration pneumonia. Am J Med. 1974;56(2):202-207. https://doi.org/10.1016/0002-9343(74)90598-1.
7. Lode H. Microbiological and clinical aspects of aspiration pneumonia. J Antimicrob Chemother. 1988;21:83-90. https://doi.org/10.1093/jac/21.suppl_c.83.
8. Brook I. Treatment of aspiration or tracheostomy-associated pneumonia in neurologically impaired children: effect of antimicrobials effective against anaerobic bacteria. Int J Pediatr Otorhinolaryngol. 1996;35(2):171-177. https://doi.org/10.1016/0165-5876(96)01332-8.
9. Jacobson SJ, Griffiths K, Diamond S, et al. A randomized controlled trial of penicillin vs clindamycin for the treatment of aspiration pneumonia in children. Arch Pediatr Adolesc Med. 1997;151(7):701-704. https://doi.org/10.1001/archpedi.1997.02170440063011.
10. DiBardino DM, Wunderink RG. Aspiration pneumonia: a review of modern trends. J Crit Care. 2015;30(1):40-48. https://doi.org/10.1016/j.jcrc.2014.07.011.
11. Gerdung CA, Tsang A, Yasseen AS, 3rd, Armstrong K, McMillan HJ, Kovesi T. Association between chronic aspiration and chronic airway infection with Pseudomonas aeruginosa and other Gram-negative bacteria in children with cerebral palsy. Lung. 2016;194(2):307-314. https://doi.org/10.1007/s00408-016-9856-5.
12. Thorburn K, Jardine M, Taylor N, Reilly N, Sarginson RE, van Saene HK. Antibiotic-resistant bacteria and infection in children with cerebral palsy requiring mechanical ventilation. Pedr Crit Care Med. 2009;10(2):222-226. https://doi.org/10.1097/PCC.0b013e31819368ac.
13. Lanspa MJ, Jones BE, Brown SM, Dean NC. Mortality, morbidity, and disease severity of patients with aspiration pneumonia. J Hosp Med. 2013;8(2):83-90. https://doi.org/10.1002/jhm.1996.
14. Lanspa MJ, Peyrani P, Wiemken T, Wilson EL, Ramirez JA, Dean NC. Characteristics associated with clinician diagnosis of aspiration pneumonia: a descriptive study of afflicted patients and their outcomes. J Hosp Med. 2015;10(2):90-96. https://doi.org/10.1002/jhm.2280.
15. Berry JG, Graham RJ, Roberson DW, et al. Patient characteristics associated with in-hospital mortality in children following tracheotomy. Arch Dis Child. 2010;95(9):703-710.
16. Berry JG, Graham DA, Graham RJ, et al. Predictors of clinical outcomes and hospital resource use of children after tracheotomy. Pediatrics. 2009;124(2):563-572. https://doi.org/10.1136/adc.2009.180836.
17. Balamuth F, Weiss SL, Hall M, et al. Identifying pediatric severe sepsis and septic shock: Accuracy of diagnosis codes. J Pediatr. 2015;167(6):1295-1300 e1294. https://doi.org/10.1016/j.jpeds.2015.09.027.
18. American Academy of Pediatrics., Pickering LK, American Academy of Pediatrics. Committee on Infectious Diseases. In: Red book : 2012 report of the Committee on Infectious Diseases. 29th ed. Elk Grove Village: American Academy of Pediatrics; 2012.
19. Gilbert DN. The Sanford Guide to Antimicrobial Therapy 2014. 44th ed. Sperryville: Antimicrobial Therapy, Inc; 2011.
20. Marik PE. Aspiration pneumonitis and aspiration pneumonia. N Engl J Med. 2001;344(9):665-671. https://doi.org/10.1056/NEJM200103013440908.
21. Feudtner C, Feinstein JA, Zhong W, Hall M, Dai D. Pediatric complex chronic conditions classification system version 2: updated for ICD-10 and complex medical technology dependence and transplantation. BMC Pediatrics. 2014;14:199. https://doi.org/10.1186/1471-2431-14-199.
22. Feudtner C, Hays RM, Haynes G, Geyer JR, Neff JM, Koepsell TD. Deaths attributed to pediatric complex chronic conditions: national trends and implications for supportive care services. Pediatrics. 2001;107(6):E99. https://doi.org/10.1542/peds.107.6.e99.
23. Feinstein JA, Russell S, DeWitt PE, Feudtner C, Dai D, Bennett TD. R package for pediatric complex chronic condition classification. JAMA Pediatr. 2018;172(6):596-598. https://doi.org/10.1001/jamapediatrics.2018.0256.
24. Berry JG, Hall DE, Kuo DZ, Cohen E, Agrawal R, Feudtner C, Hall M, Kueser J, Kaplan W, Neff J. Hospital utilization and characteristics of patients experiencing recurrent readmissions within children’s hospitals. JAMA. 2011;305(7):682-690. https://doi.org/10.1001/jama.2011.122.
25. Shah SS, Hall M, Newland JG, et al. Comparative effectiveness of pleural drainage procedures for the treatment of complicated pneumonia in childhood. J Hosp Med. 2011;6(5):256-263. https://doi.org/10.1002/jhm.872.
26. Child Health Corporation of America. CTC™ 2010 Code Structure: Module 5 Clinical Services. 2010 January 4; Available at https://sharepoint.chca.com/CHCAForums/PerformanceImprovement/PHIS/Reference Library/CTC Resources/Forms/AllItems.aspx Version: Modified.
27. Bradley JS, Byington CL, Shah SS, et al. The management of community-acquired pneumonia in infants and children older than 3 months of age: clinical practice guidelines by the Pediatric Infectious Diseases Society and the Infectious Diseases Society of America. Clin Infect Dis. 2011;53(7):e25-76. https://doi.org/10.1093/cid/cir531.
28. Brook I. Bacterial colonization, tracheobronchitis, and pneumonia following tracheostomy and long-term intubation in pediatric patients. Chest. 1979;76(4):420-424.
29. Waybright RA, Coolidge W, Johnson TJ. Treatment of clinical aspiration: a reappraisal. Am J Health Syst Pharm. 2013;70(15):1291-1300. https://doi.org/10.2146/ajhp120319.
30. Brook I, Finegold SM. Bacteriology of aspiration pneumonia in children. Pediatrics. 1980;65(6):1115-1120.
31. Wei C, Cheng Z, Zhang L, Yang J. Microbiology and prognostic factors of hospital- and community-acquired aspiration pneumonia in respiratory intensive care unit. Am J Infect Control. 2013;41(10):880-884. https://doi.org/10.1016/j.ajic.2013.01.007.
32. El-Solh AA, Pietrantoni C, Bhat A, et al. Microbiology of severe aspiration pneumonia in institutionalized elderly. Am J Respir Crit Care Med. 2003;167(12):1650-1654. https://doi.org/10.1164/rccm.200212-1543OC.
33. Tokuyasu H, Harada T, Watanabe E, et al. Effectiveness of meropenem for the treatment of aspiration pneumonia in elderly patients. Intern Med. 2009;48(3):129-135. https://doi.org/10.2169/internalmedicine.48.1308.
34. Ott SR, Allewelt M, Lorenz J, Reimnitz P, Lode H, German Lung Abscess Study Group. Moxifloxacin vs ampicillin/sulbactam in aspiration pneumonia and primary lung abscess. Infection. 2008;36(1):23-30. https://doi.org/10.1007/s15010-007-7043-6.
35. Kadowaki M, Demura Y, Mizuno S, et al. Reappraisal of clindamycin IV monotherapy for treatment of mild-to-moderate aspiration pneumonia in elderly patients. Chest. 2005;127(4):1276-1282. https://doi.org/10.1016/j.chest.2017.05.019.
36. Marik PE, Careau P. The role of anaerobes in patients with ventilator-associated pneumonia and aspiration pneumonia: a prospective study. Chest. 1999;115(1):178-183. https://doi.org/10.1378/chest.115.1.178.
37. Mier L, Dreyfuss D, Darchy B, et al. Is penicillin G an adequate initial treatment for aspiration pneumonia? A prospective evaluation using a protected specimen brush and quantitative cultures. Intensive Care Med. 1993;19(5):279-284. https://doi.org/10.1007/bf01690548.
38. Ashkenazi-Hoffnung L, Ari A, Bilavsky E, Scheuerman O, Amir J, Prais D. Pseudomonas aeruginosa identified as a key pathogen in hospitalised children with aspiration pneumonia and a high aspiration risk. Acta Paediatr. 2016;105(12):e588-e592. https://doi.org/10.1111/apa.13523.
39. Bartlett JG, Gorbach SL, Tally FP, Finegold SM. Bacteriology and treatment of primary lung abscess. Am Rev Respir Dis. 1974;109(5):510-518. https://doi.org/10.1164/arrd.1974.109.5.510.
40. Russell CJ, Simon TD, Mamey MR, Newth CJL, Neely MN. Pseudomonas aeruginosa and post-tracheotomy bacterial respiratory tract infection readmissions. Pediatr Pulmonol. 2017;52(9):1212-1218. https://doi.org/10.1002/ppul.23716.
41. Russell CJ, Mamey MR, Koh JY, Schrager SM, Neely MN, Wu S. Length of stay and hospital revisit after bacterial tracheostomy-associated respiratory tract infection hospitalizations. Hosp Pediatr. Hosp Pediatr. 2018;8(2):72-80. https://doi.org/10.1542/hpeds.2017-0106.
42. Russell CJ, Mack WJ, Schrager SM, Wu S. Care variations and outcomes for children hospitalized with bacterial tracheostomy-associated respiratory infections. Hosp Pediatr. 2017;7(1):16-23. https://doi.org/10.1542/hpeds.2016-0104.

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Emergency Transfers: An Important Predictor of Adverse Outcomes in Hospitalized Children

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Unrecognized in-hospital deterioration can result in tragic consequences for pediatric patients. The majority of deterioration events have antecedents such as increasingly abnormal vital signs and new concerns from nurses.1 Recent meta-analyses have shown that rapid response systems (RRSs), which include trigger mechanisms such as a pediatric early warning score (PEWS), are associated with a reduced rate of arrests and in-hospital mortality.2,3 Cardiopulmonary arrest rates are useful metrics to judge the effectiveness of the system to identify and respond to deteriorating adult patients; however, there are important challenges to their use as an outcome measure in pediatrics. Arrests, which have been relatively uncommon in pediatric patients, are now even less frequent since the adoption of a RRS in the majority of children’s hospitals.4,5 Several innovations in these systems will be context-dependent and hence best first evaluated in a single center, where arrests outside of the intensive care unit (ICU) may occur rarely. Identification of valid, more frequent proximal measures to arrests may better identify the risk factors for deterioration. This could potentially inform quality improvement efforts to mitigate clinical deterioration.

Bonafide et al. at the Children’s Hospital of Philadelphia developed and validated the critical deterioration event (CDE) metric, demonstrating that children who were transferred to the ICU and who received noninvasive ventilation, intubation, or vasopressor initiation within 12 hours of transfer had a >13-fold increased risk of in-hospital mortality.6 At Cincinnati Children’s Hospital Medical Center, an additional proximal outcome measure was developed for unrecognized clinical deterioration, now termed emergency transfers (ETs).7-9 An ET is defined as any patient transferred to the ICU where the patient received intubation, inotropes, or three or more fluid boluses in the first hour after arrival or before transfer.9 Improvement science work that aimed at increasing clinician situation awareness was associated with a reduction in ETs,8 but the association of ETs with mortality or other healthcare utilization outcomes is unknown. The objective of this study was to determine the predictive validity of an ET on in-hospital mortality, ICU length of stay (LOS), and overall hospital LOS.

METHODS

We conducted a case–control study at Cincinnati Children’s Hospital, a free-standing tertiary care children’s hospital. Our center has had an ICU-based RRS in place since 2005. In 2009, we eliminated the ICU consult such that each floor-to-ICU transfer is evaluated by the RRS. Nurses calculate a Monaghan PEWS every four hours on the majority of nursing units.

Patients of all ages cared for outside of the ICU at any point in their hospitalization from January 1, 2013, to July 31, 2017, were eligible for inclusion. There were no other exclusion criteria. The ICU included both the pediatric ICU and the cardiac ICU.

 

 

Cases

We identified all ET cases from an existing situation awareness database in which each RRS call is entered by the hospital nursing supervisor, whose role includes responding to each RRS activation. If the patient transfer meets the ET criteria, the nurse indicates this in the database. Each ET entry is later confirmed for assurance purposes by the nurse leader of the RRS committee (RG). For the purposes of this study, all records were again reviewed and validated using manual chart review in the electronic health record (Epic Systems, Verona, Wisconsin).

Controls

We identified nonemergent ICU transfers to serve as controls and matched those to ET in cases to limit the impact of confounders that may increase the likelihood of both an ET and a negative outcome such as ICU mortality. We identified up to three controls for each case from our database and matched in terms of age group (within five years of age), hospital unit before transfer, and time of year (within three months of ET). These variables were chosen to adjust for the impact of age, diversity of disease (as hospital units are generally organized by organ system of illness), and seasonality on outcomes.

Outcome Measures

Posttransfer LOS in the ICU, posttransfer hospital LOS, and in-hospital mortality were the primary outcome measures. Patient demographics, specific diagnoses, and number of medical conditions were a priori defined as covariates of interest. Data for each case and control were entered into a secure, web-based Research Electronic Data Capture (REDCap) database.

Analysis

Descriptive data were summarized using counts and percentages for categorical variables and medians and ranges for continuous variables due to nonnormal distributions. Chi-square test was used to compare in-hospital mortality between the ETs and the controls. The Wilcoxon rank-sum test was used to compare LOS between ETs and controls. All data analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, North Carolina).

RESULTS

A total of 45 ETs were identified, and 110 controls were matched. Patient demographics were similar among all cases and controls (P > .05). Patients with ETs had a median age of seven years (interquartile range: 3-18 years), and 51% of them were males. The majority of patients among our examined cases were white (68%) and non-Hispanic (93%). There was no statistical difference in insurance between the ETs and the controls. When evaluating the hospital unit before the transfer, ETs occurred most commonly in the Cardiology (22%), Hematology/Oncology (22%), and Neuroscience (16%) units.

ETs stayed longer in the ICU than non-ETs [median of 4.9 days vs 2.2 days, P = .001; Figure (A)]. Similarly, ET cases had a significantly longer posttransfer hospital LOS [median of 35 days vs 21 days, P = .001; Figure (B)]. ETs had a 22% in-hospital mortality rate, compared with 9% in-hospital mortality in the matched controls (P = .02; Table).

DISCUSSION

Children who experienced an ET had a significantly longer ICU LOS, a longer posttransfer LOS, and a higher in-hospital mortality than the matched controls who were also transferred to the ICU. Researchers and improvement science teams at multiple hospitals have demonstrated that interventions targeting improved situation awareness can reduce ETs; we have demonstrated that reducing ETs may reduce subsequent adverse outcomes.8,10

 

 

These findings provide additional support for the use of the ET metric in children’s hospitals as a proximal measure for significant clinical deterioration. We found mortality rates that were overall high for a children’s hospital (22% in ET cases and 9% among controls) compared with a national average mortality rate of 2.3% in pediatric ICUs.11 This is likely due to the study sample containing a significant proportion of children with medical complexity.

Aoki et al. recently demonstrated that ETs, compared with non-ETs, were associated with longer LOS and higher mortality in a bivariate analysis.12 In our study, we found similar results with the important addition that these findings were robust when ETs were compared with matched controls who were likely at a higher risk of poor outcomes than ICU transfers in general. In addition, we demonstrated that ETs were associated with adverse outcomes in a United States children’s hospital with a mature, long-standing RRS process. As ETs are considerably more common than cardiac and respiratory arrests, use of the ET metric in children’s hospitals may enable more rapid learning and systems improvement implementations. We also found that most of the children with ETs present from units that care for children with substantial medical complexity, including Cardiology, Hematology/Oncology, and Neurosciences. Future work should continue to examine the relationship between medical complexity and ET risk.

The ET metric is complementary to the CDE measure developed by Bonafide et al. Both metrics capture potential events of unrecognized clinical deterioration, and both offer researchers the opportunity to better understand and improve their RRSs. Both ETs and CDEs are more common than arrests, and CDEs are more common than ETs. ETs, which by definition occur in the first hour of ICU care, are likely a more specific measure of unrecognized clinical deterioration. CDEs will capture therapies that may have been started up to 12 hours after transfer and thus are possibly more sensitive to identify unrecognized clinical deterioration. However, CDEs also may encompass some patients who arrived at the ICU after prompt recognition and then had a subacute deterioration in the ICU.

The maturity of the RRS and the bandwidth of teams to collect data may inform which metric(s) are best for individual centers. As ETs are less common and likely more specific to unrecognized clinical deterioration, they might be the first tracked as a center improves its RRS through QI methods. Alternatively, CDEs may be a useful metric for centers where unrecognized clinical deterioration is less common or in research studies where this more common outcome would lead to more power to detect the effect of interventions to improve care.

Our study had several limitations. Data collection was confined to one tertiary care children’s hospital with a high burden of complex cardiac and oncology care. The results may not generalize well to children hospitalized in smaller or community hospitals or in hospitals without a mature RRS. There is also the possibility of misclassification of covariates and outcomes, but any misclassification would likely be nondifferential and bias toward the null. Matching was not possible based on exact diagnosis, and the unit is a good but imperfect proxy for diagnosis grouping. At our center, overflow of patients into the Cardiology and Hematology/Oncology units is uncommon, mitigating this partially, although residual confounding may remain. The finding that ETs are associated with adverse outcomes does not necessarily mean that these events were preventable; however, it is important and encouraging that the rate of ETs has been reduced at two centers using improvement science interventions.8,10

 

 

CONCLUSION

Patients who experienced an ET had a significantly higher likelihood of in-hospital mortality, spent more time in the ICU, and had a longer hospital LOS posttransfer than matched controls. The use of the ET metric in children’s hospitals would allow for further analysis of such patients in hopes of identifying clinical characteristics that serve as predictors of deterioration. This may facilitate better risk stratification in the clinical system as well as enable more rapid learning and systems improvements targeted toward preventing unrecognized clinical deterioration.

Disclosures

Dr. Hussain, Dr. Sosa, Dr. Ambroggio, and Mrs. Gallagher have nothing to disclose. Patrick Brady reports grants from the Agency for Healthcare Research and Quality, outside the submitted work. The authors certify that this submission is not under review by any other publication. The author team has no conflicts of interest to disclose.

Funding

Ms. Hussain was supported by the Society of Hospital Medicine’s Student Hospitalist Scholar Grant Program in 2017. Dr. Brady receives career development support from AHRQ K08-HS023827. The project described was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health, under Award Number 5UL1TR001425-04. The content is solely the responsibility of the authors and does not necessarily represent the official views of the SHM, AHRQ, or NIH.

 

References

1. Schein RM, Hazday N, Pena M, Ruben BH, Sprung CL. Clinical antecedents to in-hospital cardiopulmonary arrest. Chest. 1990;98(6):1388-1392. https://doi.org/10.1378/chest.98.6.1388.
2. Maharaj R, Raffaele I, Wendon J. Rapid response systems: a systematic review and meta-analysis. Crit Care. 2015;19:254. https://doi.org/10.1186/s13054-015-0973-y.
3. Bonafide CP, Roland D, Brady PW. Rapid response systems 20 years later: new approaches, old challenges. JAMA Pediatrics. 2016;170(8):729-730. https://doi.org/10.1001/jamapediatrics.2016.0398.
4. Hayes LW, Dobyns EL, DiGiovine B, et al. A multicenter collaborative approach to reducing pediatric codes outside the ICU. Pediatrics. 2012;129(3):e785-e791. https://doi.org/10.1542/peds.2011-0227.
5. Raymond TT, Bonafide CP, Praestgaard A, et al. Pediatric medical emergency team events and outcomes: a report of 3647 events from the American Heart Association’s get with the guidelines-resuscitation registry. Hosp Pediatr. 2016;6(2):57-64. https://doi.org/10.1542/hpeds.2015-0132.
6. Bonafide CP, Roberts KE, Priestley MA, et al. Development of a pragmatic measure for evaluating and optimizing rapid response systems. Pediatrics. 2012;129(4):e874-e881. https://doi.org/10.1542/peds.2011-2784.
7. Brady PW, Goldenhar LM. A qualitative study examining the influences on situation awareness and the identification, mitigation and escalation of recognised patient risk. BMJ Qual Saf. 2014;23(2):153-161. https://doi.org/10.1136/bmjqs-2012-001747.
8. Brady PW, Muething S, Kotagal U, et al. Improving situation awareness to reduce unrecognized clinical deterioration and serious safety events. Pediatrics. 2013;131(1):e298-e308. https://doi.org/10.1542/peds.2012-1364.
9. Brady PW, Wheeler DS, Muething SE, Kotagal UR. Situation awareness: a new model for predicting and preventing patient deterioration. Hosp Pediatr. 2014;4(3):143-146. https://doi.org/10.1542/hpeds.2013-0119.
10. McClain Smith M, Chumpia M, Wargo L, Nicol J, Bugnitz M. Watcher initiative associated with decrease in failure to rescue events in pediatric population. Hosp Pediatr. 2017;7(12):710-715. https://doi.org/10.1542/hpeds.2017-0042.
11. McCrory MC, Spaeder MC, Gower EW, et al. Time of admission to the PICU and mortality. Pediatr Crit Care Med. 2017;18(10):915-923. https://doi.org/10.1097/PCC.0000000000001268.
12. Aoki Y, Inata Y, Hatachi T, Shimizu Y, Takeuchi M. Outcomes of ‘unrecognised situation awareness failures events’ in intensive care unit transfer of children in a Japanese children’s hospital. J Paediatr Child Health. 2018;55(2):213-215. https://doi.org/10.1111/jpc.14185.

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Unrecognized in-hospital deterioration can result in tragic consequences for pediatric patients. The majority of deterioration events have antecedents such as increasingly abnormal vital signs and new concerns from nurses.1 Recent meta-analyses have shown that rapid response systems (RRSs), which include trigger mechanisms such as a pediatric early warning score (PEWS), are associated with a reduced rate of arrests and in-hospital mortality.2,3 Cardiopulmonary arrest rates are useful metrics to judge the effectiveness of the system to identify and respond to deteriorating adult patients; however, there are important challenges to their use as an outcome measure in pediatrics. Arrests, which have been relatively uncommon in pediatric patients, are now even less frequent since the adoption of a RRS in the majority of children’s hospitals.4,5 Several innovations in these systems will be context-dependent and hence best first evaluated in a single center, where arrests outside of the intensive care unit (ICU) may occur rarely. Identification of valid, more frequent proximal measures to arrests may better identify the risk factors for deterioration. This could potentially inform quality improvement efforts to mitigate clinical deterioration.

Bonafide et al. at the Children’s Hospital of Philadelphia developed and validated the critical deterioration event (CDE) metric, demonstrating that children who were transferred to the ICU and who received noninvasive ventilation, intubation, or vasopressor initiation within 12 hours of transfer had a >13-fold increased risk of in-hospital mortality.6 At Cincinnati Children’s Hospital Medical Center, an additional proximal outcome measure was developed for unrecognized clinical deterioration, now termed emergency transfers (ETs).7-9 An ET is defined as any patient transferred to the ICU where the patient received intubation, inotropes, or three or more fluid boluses in the first hour after arrival or before transfer.9 Improvement science work that aimed at increasing clinician situation awareness was associated with a reduction in ETs,8 but the association of ETs with mortality or other healthcare utilization outcomes is unknown. The objective of this study was to determine the predictive validity of an ET on in-hospital mortality, ICU length of stay (LOS), and overall hospital LOS.

METHODS

We conducted a case–control study at Cincinnati Children’s Hospital, a free-standing tertiary care children’s hospital. Our center has had an ICU-based RRS in place since 2005. In 2009, we eliminated the ICU consult such that each floor-to-ICU transfer is evaluated by the RRS. Nurses calculate a Monaghan PEWS every four hours on the majority of nursing units.

Patients of all ages cared for outside of the ICU at any point in their hospitalization from January 1, 2013, to July 31, 2017, were eligible for inclusion. There were no other exclusion criteria. The ICU included both the pediatric ICU and the cardiac ICU.

 

 

Cases

We identified all ET cases from an existing situation awareness database in which each RRS call is entered by the hospital nursing supervisor, whose role includes responding to each RRS activation. If the patient transfer meets the ET criteria, the nurse indicates this in the database. Each ET entry is later confirmed for assurance purposes by the nurse leader of the RRS committee (RG). For the purposes of this study, all records were again reviewed and validated using manual chart review in the electronic health record (Epic Systems, Verona, Wisconsin).

Controls

We identified nonemergent ICU transfers to serve as controls and matched those to ET in cases to limit the impact of confounders that may increase the likelihood of both an ET and a negative outcome such as ICU mortality. We identified up to three controls for each case from our database and matched in terms of age group (within five years of age), hospital unit before transfer, and time of year (within three months of ET). These variables were chosen to adjust for the impact of age, diversity of disease (as hospital units are generally organized by organ system of illness), and seasonality on outcomes.

Outcome Measures

Posttransfer LOS in the ICU, posttransfer hospital LOS, and in-hospital mortality were the primary outcome measures. Patient demographics, specific diagnoses, and number of medical conditions were a priori defined as covariates of interest. Data for each case and control were entered into a secure, web-based Research Electronic Data Capture (REDCap) database.

Analysis

Descriptive data were summarized using counts and percentages for categorical variables and medians and ranges for continuous variables due to nonnormal distributions. Chi-square test was used to compare in-hospital mortality between the ETs and the controls. The Wilcoxon rank-sum test was used to compare LOS between ETs and controls. All data analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, North Carolina).

RESULTS

A total of 45 ETs were identified, and 110 controls were matched. Patient demographics were similar among all cases and controls (P > .05). Patients with ETs had a median age of seven years (interquartile range: 3-18 years), and 51% of them were males. The majority of patients among our examined cases were white (68%) and non-Hispanic (93%). There was no statistical difference in insurance between the ETs and the controls. When evaluating the hospital unit before the transfer, ETs occurred most commonly in the Cardiology (22%), Hematology/Oncology (22%), and Neuroscience (16%) units.

ETs stayed longer in the ICU than non-ETs [median of 4.9 days vs 2.2 days, P = .001; Figure (A)]. Similarly, ET cases had a significantly longer posttransfer hospital LOS [median of 35 days vs 21 days, P = .001; Figure (B)]. ETs had a 22% in-hospital mortality rate, compared with 9% in-hospital mortality in the matched controls (P = .02; Table).

DISCUSSION

Children who experienced an ET had a significantly longer ICU LOS, a longer posttransfer LOS, and a higher in-hospital mortality than the matched controls who were also transferred to the ICU. Researchers and improvement science teams at multiple hospitals have demonstrated that interventions targeting improved situation awareness can reduce ETs; we have demonstrated that reducing ETs may reduce subsequent adverse outcomes.8,10

 

 

These findings provide additional support for the use of the ET metric in children’s hospitals as a proximal measure for significant clinical deterioration. We found mortality rates that were overall high for a children’s hospital (22% in ET cases and 9% among controls) compared with a national average mortality rate of 2.3% in pediatric ICUs.11 This is likely due to the study sample containing a significant proportion of children with medical complexity.

Aoki et al. recently demonstrated that ETs, compared with non-ETs, were associated with longer LOS and higher mortality in a bivariate analysis.12 In our study, we found similar results with the important addition that these findings were robust when ETs were compared with matched controls who were likely at a higher risk of poor outcomes than ICU transfers in general. In addition, we demonstrated that ETs were associated with adverse outcomes in a United States children’s hospital with a mature, long-standing RRS process. As ETs are considerably more common than cardiac and respiratory arrests, use of the ET metric in children’s hospitals may enable more rapid learning and systems improvement implementations. We also found that most of the children with ETs present from units that care for children with substantial medical complexity, including Cardiology, Hematology/Oncology, and Neurosciences. Future work should continue to examine the relationship between medical complexity and ET risk.

The ET metric is complementary to the CDE measure developed by Bonafide et al. Both metrics capture potential events of unrecognized clinical deterioration, and both offer researchers the opportunity to better understand and improve their RRSs. Both ETs and CDEs are more common than arrests, and CDEs are more common than ETs. ETs, which by definition occur in the first hour of ICU care, are likely a more specific measure of unrecognized clinical deterioration. CDEs will capture therapies that may have been started up to 12 hours after transfer and thus are possibly more sensitive to identify unrecognized clinical deterioration. However, CDEs also may encompass some patients who arrived at the ICU after prompt recognition and then had a subacute deterioration in the ICU.

The maturity of the RRS and the bandwidth of teams to collect data may inform which metric(s) are best for individual centers. As ETs are less common and likely more specific to unrecognized clinical deterioration, they might be the first tracked as a center improves its RRS through QI methods. Alternatively, CDEs may be a useful metric for centers where unrecognized clinical deterioration is less common or in research studies where this more common outcome would lead to more power to detect the effect of interventions to improve care.

Our study had several limitations. Data collection was confined to one tertiary care children’s hospital with a high burden of complex cardiac and oncology care. The results may not generalize well to children hospitalized in smaller or community hospitals or in hospitals without a mature RRS. There is also the possibility of misclassification of covariates and outcomes, but any misclassification would likely be nondifferential and bias toward the null. Matching was not possible based on exact diagnosis, and the unit is a good but imperfect proxy for diagnosis grouping. At our center, overflow of patients into the Cardiology and Hematology/Oncology units is uncommon, mitigating this partially, although residual confounding may remain. The finding that ETs are associated with adverse outcomes does not necessarily mean that these events were preventable; however, it is important and encouraging that the rate of ETs has been reduced at two centers using improvement science interventions.8,10

 

 

CONCLUSION

Patients who experienced an ET had a significantly higher likelihood of in-hospital mortality, spent more time in the ICU, and had a longer hospital LOS posttransfer than matched controls. The use of the ET metric in children’s hospitals would allow for further analysis of such patients in hopes of identifying clinical characteristics that serve as predictors of deterioration. This may facilitate better risk stratification in the clinical system as well as enable more rapid learning and systems improvements targeted toward preventing unrecognized clinical deterioration.

Disclosures

Dr. Hussain, Dr. Sosa, Dr. Ambroggio, and Mrs. Gallagher have nothing to disclose. Patrick Brady reports grants from the Agency for Healthcare Research and Quality, outside the submitted work. The authors certify that this submission is not under review by any other publication. The author team has no conflicts of interest to disclose.

Funding

Ms. Hussain was supported by the Society of Hospital Medicine’s Student Hospitalist Scholar Grant Program in 2017. Dr. Brady receives career development support from AHRQ K08-HS023827. The project described was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health, under Award Number 5UL1TR001425-04. The content is solely the responsibility of the authors and does not necessarily represent the official views of the SHM, AHRQ, or NIH.

 

Unrecognized in-hospital deterioration can result in tragic consequences for pediatric patients. The majority of deterioration events have antecedents such as increasingly abnormal vital signs and new concerns from nurses.1 Recent meta-analyses have shown that rapid response systems (RRSs), which include trigger mechanisms such as a pediatric early warning score (PEWS), are associated with a reduced rate of arrests and in-hospital mortality.2,3 Cardiopulmonary arrest rates are useful metrics to judge the effectiveness of the system to identify and respond to deteriorating adult patients; however, there are important challenges to their use as an outcome measure in pediatrics. Arrests, which have been relatively uncommon in pediatric patients, are now even less frequent since the adoption of a RRS in the majority of children’s hospitals.4,5 Several innovations in these systems will be context-dependent and hence best first evaluated in a single center, where arrests outside of the intensive care unit (ICU) may occur rarely. Identification of valid, more frequent proximal measures to arrests may better identify the risk factors for deterioration. This could potentially inform quality improvement efforts to mitigate clinical deterioration.

Bonafide et al. at the Children’s Hospital of Philadelphia developed and validated the critical deterioration event (CDE) metric, demonstrating that children who were transferred to the ICU and who received noninvasive ventilation, intubation, or vasopressor initiation within 12 hours of transfer had a >13-fold increased risk of in-hospital mortality.6 At Cincinnati Children’s Hospital Medical Center, an additional proximal outcome measure was developed for unrecognized clinical deterioration, now termed emergency transfers (ETs).7-9 An ET is defined as any patient transferred to the ICU where the patient received intubation, inotropes, or three or more fluid boluses in the first hour after arrival or before transfer.9 Improvement science work that aimed at increasing clinician situation awareness was associated with a reduction in ETs,8 but the association of ETs with mortality or other healthcare utilization outcomes is unknown. The objective of this study was to determine the predictive validity of an ET on in-hospital mortality, ICU length of stay (LOS), and overall hospital LOS.

METHODS

We conducted a case–control study at Cincinnati Children’s Hospital, a free-standing tertiary care children’s hospital. Our center has had an ICU-based RRS in place since 2005. In 2009, we eliminated the ICU consult such that each floor-to-ICU transfer is evaluated by the RRS. Nurses calculate a Monaghan PEWS every four hours on the majority of nursing units.

Patients of all ages cared for outside of the ICU at any point in their hospitalization from January 1, 2013, to July 31, 2017, were eligible for inclusion. There were no other exclusion criteria. The ICU included both the pediatric ICU and the cardiac ICU.

 

 

Cases

We identified all ET cases from an existing situation awareness database in which each RRS call is entered by the hospital nursing supervisor, whose role includes responding to each RRS activation. If the patient transfer meets the ET criteria, the nurse indicates this in the database. Each ET entry is later confirmed for assurance purposes by the nurse leader of the RRS committee (RG). For the purposes of this study, all records were again reviewed and validated using manual chart review in the electronic health record (Epic Systems, Verona, Wisconsin).

Controls

We identified nonemergent ICU transfers to serve as controls and matched those to ET in cases to limit the impact of confounders that may increase the likelihood of both an ET and a negative outcome such as ICU mortality. We identified up to three controls for each case from our database and matched in terms of age group (within five years of age), hospital unit before transfer, and time of year (within three months of ET). These variables were chosen to adjust for the impact of age, diversity of disease (as hospital units are generally organized by organ system of illness), and seasonality on outcomes.

Outcome Measures

Posttransfer LOS in the ICU, posttransfer hospital LOS, and in-hospital mortality were the primary outcome measures. Patient demographics, specific diagnoses, and number of medical conditions were a priori defined as covariates of interest. Data for each case and control were entered into a secure, web-based Research Electronic Data Capture (REDCap) database.

Analysis

Descriptive data were summarized using counts and percentages for categorical variables and medians and ranges for continuous variables due to nonnormal distributions. Chi-square test was used to compare in-hospital mortality between the ETs and the controls. The Wilcoxon rank-sum test was used to compare LOS between ETs and controls. All data analyses were performed using SAS version 9.4 (SAS Institute Inc., Cary, North Carolina).

RESULTS

A total of 45 ETs were identified, and 110 controls were matched. Patient demographics were similar among all cases and controls (P > .05). Patients with ETs had a median age of seven years (interquartile range: 3-18 years), and 51% of them were males. The majority of patients among our examined cases were white (68%) and non-Hispanic (93%). There was no statistical difference in insurance between the ETs and the controls. When evaluating the hospital unit before the transfer, ETs occurred most commonly in the Cardiology (22%), Hematology/Oncology (22%), and Neuroscience (16%) units.

ETs stayed longer in the ICU than non-ETs [median of 4.9 days vs 2.2 days, P = .001; Figure (A)]. Similarly, ET cases had a significantly longer posttransfer hospital LOS [median of 35 days vs 21 days, P = .001; Figure (B)]. ETs had a 22% in-hospital mortality rate, compared with 9% in-hospital mortality in the matched controls (P = .02; Table).

DISCUSSION

Children who experienced an ET had a significantly longer ICU LOS, a longer posttransfer LOS, and a higher in-hospital mortality than the matched controls who were also transferred to the ICU. Researchers and improvement science teams at multiple hospitals have demonstrated that interventions targeting improved situation awareness can reduce ETs; we have demonstrated that reducing ETs may reduce subsequent adverse outcomes.8,10

 

 

These findings provide additional support for the use of the ET metric in children’s hospitals as a proximal measure for significant clinical deterioration. We found mortality rates that were overall high for a children’s hospital (22% in ET cases and 9% among controls) compared with a national average mortality rate of 2.3% in pediatric ICUs.11 This is likely due to the study sample containing a significant proportion of children with medical complexity.

Aoki et al. recently demonstrated that ETs, compared with non-ETs, were associated with longer LOS and higher mortality in a bivariate analysis.12 In our study, we found similar results with the important addition that these findings were robust when ETs were compared with matched controls who were likely at a higher risk of poor outcomes than ICU transfers in general. In addition, we demonstrated that ETs were associated with adverse outcomes in a United States children’s hospital with a mature, long-standing RRS process. As ETs are considerably more common than cardiac and respiratory arrests, use of the ET metric in children’s hospitals may enable more rapid learning and systems improvement implementations. We also found that most of the children with ETs present from units that care for children with substantial medical complexity, including Cardiology, Hematology/Oncology, and Neurosciences. Future work should continue to examine the relationship between medical complexity and ET risk.

The ET metric is complementary to the CDE measure developed by Bonafide et al. Both metrics capture potential events of unrecognized clinical deterioration, and both offer researchers the opportunity to better understand and improve their RRSs. Both ETs and CDEs are more common than arrests, and CDEs are more common than ETs. ETs, which by definition occur in the first hour of ICU care, are likely a more specific measure of unrecognized clinical deterioration. CDEs will capture therapies that may have been started up to 12 hours after transfer and thus are possibly more sensitive to identify unrecognized clinical deterioration. However, CDEs also may encompass some patients who arrived at the ICU after prompt recognition and then had a subacute deterioration in the ICU.

The maturity of the RRS and the bandwidth of teams to collect data may inform which metric(s) are best for individual centers. As ETs are less common and likely more specific to unrecognized clinical deterioration, they might be the first tracked as a center improves its RRS through QI methods. Alternatively, CDEs may be a useful metric for centers where unrecognized clinical deterioration is less common or in research studies where this more common outcome would lead to more power to detect the effect of interventions to improve care.

Our study had several limitations. Data collection was confined to one tertiary care children’s hospital with a high burden of complex cardiac and oncology care. The results may not generalize well to children hospitalized in smaller or community hospitals or in hospitals without a mature RRS. There is also the possibility of misclassification of covariates and outcomes, but any misclassification would likely be nondifferential and bias toward the null. Matching was not possible based on exact diagnosis, and the unit is a good but imperfect proxy for diagnosis grouping. At our center, overflow of patients into the Cardiology and Hematology/Oncology units is uncommon, mitigating this partially, although residual confounding may remain. The finding that ETs are associated with adverse outcomes does not necessarily mean that these events were preventable; however, it is important and encouraging that the rate of ETs has been reduced at two centers using improvement science interventions.8,10

 

 

CONCLUSION

Patients who experienced an ET had a significantly higher likelihood of in-hospital mortality, spent more time in the ICU, and had a longer hospital LOS posttransfer than matched controls. The use of the ET metric in children’s hospitals would allow for further analysis of such patients in hopes of identifying clinical characteristics that serve as predictors of deterioration. This may facilitate better risk stratification in the clinical system as well as enable more rapid learning and systems improvements targeted toward preventing unrecognized clinical deterioration.

Disclosures

Dr. Hussain, Dr. Sosa, Dr. Ambroggio, and Mrs. Gallagher have nothing to disclose. Patrick Brady reports grants from the Agency for Healthcare Research and Quality, outside the submitted work. The authors certify that this submission is not under review by any other publication. The author team has no conflicts of interest to disclose.

Funding

Ms. Hussain was supported by the Society of Hospital Medicine’s Student Hospitalist Scholar Grant Program in 2017. Dr. Brady receives career development support from AHRQ K08-HS023827. The project described was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health, under Award Number 5UL1TR001425-04. The content is solely the responsibility of the authors and does not necessarily represent the official views of the SHM, AHRQ, or NIH.

 

References

1. Schein RM, Hazday N, Pena M, Ruben BH, Sprung CL. Clinical antecedents to in-hospital cardiopulmonary arrest. Chest. 1990;98(6):1388-1392. https://doi.org/10.1378/chest.98.6.1388.
2. Maharaj R, Raffaele I, Wendon J. Rapid response systems: a systematic review and meta-analysis. Crit Care. 2015;19:254. https://doi.org/10.1186/s13054-015-0973-y.
3. Bonafide CP, Roland D, Brady PW. Rapid response systems 20 years later: new approaches, old challenges. JAMA Pediatrics. 2016;170(8):729-730. https://doi.org/10.1001/jamapediatrics.2016.0398.
4. Hayes LW, Dobyns EL, DiGiovine B, et al. A multicenter collaborative approach to reducing pediatric codes outside the ICU. Pediatrics. 2012;129(3):e785-e791. https://doi.org/10.1542/peds.2011-0227.
5. Raymond TT, Bonafide CP, Praestgaard A, et al. Pediatric medical emergency team events and outcomes: a report of 3647 events from the American Heart Association’s get with the guidelines-resuscitation registry. Hosp Pediatr. 2016;6(2):57-64. https://doi.org/10.1542/hpeds.2015-0132.
6. Bonafide CP, Roberts KE, Priestley MA, et al. Development of a pragmatic measure for evaluating and optimizing rapid response systems. Pediatrics. 2012;129(4):e874-e881. https://doi.org/10.1542/peds.2011-2784.
7. Brady PW, Goldenhar LM. A qualitative study examining the influences on situation awareness and the identification, mitigation and escalation of recognised patient risk. BMJ Qual Saf. 2014;23(2):153-161. https://doi.org/10.1136/bmjqs-2012-001747.
8. Brady PW, Muething S, Kotagal U, et al. Improving situation awareness to reduce unrecognized clinical deterioration and serious safety events. Pediatrics. 2013;131(1):e298-e308. https://doi.org/10.1542/peds.2012-1364.
9. Brady PW, Wheeler DS, Muething SE, Kotagal UR. Situation awareness: a new model for predicting and preventing patient deterioration. Hosp Pediatr. 2014;4(3):143-146. https://doi.org/10.1542/hpeds.2013-0119.
10. McClain Smith M, Chumpia M, Wargo L, Nicol J, Bugnitz M. Watcher initiative associated with decrease in failure to rescue events in pediatric population. Hosp Pediatr. 2017;7(12):710-715. https://doi.org/10.1542/hpeds.2017-0042.
11. McCrory MC, Spaeder MC, Gower EW, et al. Time of admission to the PICU and mortality. Pediatr Crit Care Med. 2017;18(10):915-923. https://doi.org/10.1097/PCC.0000000000001268.
12. Aoki Y, Inata Y, Hatachi T, Shimizu Y, Takeuchi M. Outcomes of ‘unrecognised situation awareness failures events’ in intensive care unit transfer of children in a Japanese children’s hospital. J Paediatr Child Health. 2018;55(2):213-215. https://doi.org/10.1111/jpc.14185.

References

1. Schein RM, Hazday N, Pena M, Ruben BH, Sprung CL. Clinical antecedents to in-hospital cardiopulmonary arrest. Chest. 1990;98(6):1388-1392. https://doi.org/10.1378/chest.98.6.1388.
2. Maharaj R, Raffaele I, Wendon J. Rapid response systems: a systematic review and meta-analysis. Crit Care. 2015;19:254. https://doi.org/10.1186/s13054-015-0973-y.
3. Bonafide CP, Roland D, Brady PW. Rapid response systems 20 years later: new approaches, old challenges. JAMA Pediatrics. 2016;170(8):729-730. https://doi.org/10.1001/jamapediatrics.2016.0398.
4. Hayes LW, Dobyns EL, DiGiovine B, et al. A multicenter collaborative approach to reducing pediatric codes outside the ICU. Pediatrics. 2012;129(3):e785-e791. https://doi.org/10.1542/peds.2011-0227.
5. Raymond TT, Bonafide CP, Praestgaard A, et al. Pediatric medical emergency team events and outcomes: a report of 3647 events from the American Heart Association’s get with the guidelines-resuscitation registry. Hosp Pediatr. 2016;6(2):57-64. https://doi.org/10.1542/hpeds.2015-0132.
6. Bonafide CP, Roberts KE, Priestley MA, et al. Development of a pragmatic measure for evaluating and optimizing rapid response systems. Pediatrics. 2012;129(4):e874-e881. https://doi.org/10.1542/peds.2011-2784.
7. Brady PW, Goldenhar LM. A qualitative study examining the influences on situation awareness and the identification, mitigation and escalation of recognised patient risk. BMJ Qual Saf. 2014;23(2):153-161. https://doi.org/10.1136/bmjqs-2012-001747.
8. Brady PW, Muething S, Kotagal U, et al. Improving situation awareness to reduce unrecognized clinical deterioration and serious safety events. Pediatrics. 2013;131(1):e298-e308. https://doi.org/10.1542/peds.2012-1364.
9. Brady PW, Wheeler DS, Muething SE, Kotagal UR. Situation awareness: a new model for predicting and preventing patient deterioration. Hosp Pediatr. 2014;4(3):143-146. https://doi.org/10.1542/hpeds.2013-0119.
10. McClain Smith M, Chumpia M, Wargo L, Nicol J, Bugnitz M. Watcher initiative associated with decrease in failure to rescue events in pediatric population. Hosp Pediatr. 2017;7(12):710-715. https://doi.org/10.1542/hpeds.2017-0042.
11. McCrory MC, Spaeder MC, Gower EW, et al. Time of admission to the PICU and mortality. Pediatr Crit Care Med. 2017;18(10):915-923. https://doi.org/10.1097/PCC.0000000000001268.
12. Aoki Y, Inata Y, Hatachi T, Shimizu Y, Takeuchi M. Outcomes of ‘unrecognised situation awareness failures events’ in intensive care unit transfer of children in a Japanese children’s hospital. J Paediatr Child Health. 2018;55(2):213-215. https://doi.org/10.1111/jpc.14185.

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Pneumonia Guideline Therapy Outcomes

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Hospital outcomes associated with guideline‐recommended antibiotic therapy for pediatric pneumonia

Community‐acquired pneumonia (CAP) is a common and serious infection in children. With more than 150,000 children requiring hospitalization annually, CAP is the fifth most prevalent and the second most costly diagnosis of all pediatric hospitalizations in the United States.[1, 2, 3]

In August 2011, the Pediatric Infectious Diseases Society (PIDS) and the Infectious Diseases Society of America (IDSA) published an evidence‐based guideline for the management of CAP in children. This guideline recommended that fully immunized children without underlying complications who require hospitalization receive an aminopenicillin as first‐line antibiotic therapy.[4] Additionally, the guideline recommends empirically adding a macrolide to an aminopenicillin when atypical pneumonia is a diagnostic consideration.

This recommendation was a substantial departure from practice for hospitals nationwide, as a multicenter study of children's hospitals (20052010) demonstrated that <10% of patients diagnosed with CAP received aminopenicillins as empiric therapy.[5] Since publication of the PIDS/IDSA guidelines, the use of aminopenicillins has increased significantly across institutions, but the majority of hospitalized patients still receive broad‐spectrum cephalosporin therapy for CAP.[6]

At baseline, 30% of patients hospitalized with CAP received guideline‐recommended antibiotic therapy at our institution. Through the use of quality‐improvement methods, the proportion of patients receiving guideline‐recommended therapy increased to 100%.[7] The objective of this study was to ensure that there were not unintended negative consequences to guideline implementation. Specifically, we sought to identify changes in length of stay (LOS), hospital costs, and treatment failures associated with use of guideline‐recommended antibiotic therapy for children hospitalized with uncomplicated CAP.

METHODS

Study Design and Study Population

This retrospective cohort study included children age 3 months to 18 years, hospitalized with CAP, between May 2, 2011 and July 30, 2012, at Cincinnati Children's Hospital Medical Center (CCHMC), a 512‐bed free‐standing children's hospital. The CCHMC Institutional Review Board approved this study with a waiver of informed consent.

Patients were eligible for inclusion if they were admitted to the hospital for inpatient or observation level care with a primary or secondary International Classification of Disease, 9th Revision discharge diagnosis code of pneumonia (480.02, 480.89, 481, 482.0, 482.30‐2, 482.41‐2, 482.83, 482.8990, 483.8, 484.3, 485, 486, 487.0) or effusion/empyema (510.0, 510.9, 511.01, 511.89, 513).[8] Patients with complex chronic conditions[9] were excluded. Medical records of eligible patients (n=260) were reviewed by 2 members of the study team to ensure that patients fell into the purview of the guideline. Patients who did not receive antibiotics (n=11) or for whom there was documented concern for aspiration (n=1) were excluded. Additionally, patients with immunodeficiency (n=1) or who had not received age‐appropriate vaccinations (n=2), and patients who required intensive care unit admission on presentation (n=17) or who had a complicated pneumonia, defined by presence of moderate or large pleural effusion at time of admission (n=8), were also excluded.[7] Finally, for patients with multiple pneumonia admissions, only the index visit was included; subsequent visits occurring within 30 days of discharge were considered readmissions.

Treatment Measure

The primary exposure of interest was empiric antibiotic therapy upon hospital admission. Antibiotic therapy was classified as guideline recommended or nonguideline recommended. Guideline‐recommended therapy was defined as follows:

  1. For children without drug allergies: ampicillin (200 mg/kg/day intravenously) or amoxicillin (90 mg/kg/day orally);
  2. For children with penicillin allergy: ceftriaxone (50100 mg/kg/day intravenously or intramuscularly) or cefdinir (14 mg/kg/day orally);
  3. For children with penicillin and cephalosporin allergy: clindamycin (40 mg/kg/day orally or intravenously); and
  4. Or azithromycin (10 mg/kg/day orally or intravenously on day 1) in combination with antibiotic category 1 or 2 or 3 above.

 

Outcome Measures

The primary outcomes examined were hospital LOS, total cost of hospitalization, and inpatient pharmacy costs. LOS was measured in hours and defined as the difference in time between departure from and arrival to the inpatient unit. Total cost of index hospitalization included both direct and indirect costs, obtained from the Centers for Medicare & Medicaid Services' Relative Value Units data for Current Procedural Terminology codes.[10]

Secondary outcomes included broadening of antibiotic therapy during the hospital course, pneumonia‐related emergency department (ED) revisits within 30 days, and pneumonia‐related inpatient readmissions within 30 days. Broadening of antibiotic therapy was defined as addition of a second antibiotic (eg, adding azithromycin on day 3 of hospitalization) or change in empiric antibiotic to a class with broader antimicrobial activity (eg, ampicillin to ceftriaxone) at any time during hospitalization. As our study population included only patients with uncomplicated pneumonia at the time of admission, this outcome was used to capture possible treatment failure. ED revisits and inpatient readmissions were reviewed by 3 investigators to identify pneumonia‐related visits. To encompass all possible treatment failures, all respiratory‐related complaints (eg, wheezing, respiratory distress) were considered as pneumonia‐related. Disagreements were resolved by group discussion.

Covariates

Severity of illness on presentation was evaluated using the Emergency Severity Index version 4,[11] abnormal vital signs on presentation (as defined by Pediatric Advanced Life Support age‐specific criteria[12]), and need for oxygen in the first 24 hours of hospitalization. Supplemental oxygen is administered for saturations <91% per protocol at our institution. The patient's highest Pediatric Early Warning Scale score[13] during hospitalization was used as a proxy for disease severity. Exam findings on presentation (eg, increased respiratory effort, rales, wheezing) were determined through chart review. Laboratory tests and radiologic imaging variables included complete blood cell count, blood culture, chest radiograph, chest ultrasound, and chest computed tomography. Abnormal white blood cell count was defined as <5000 or >15,000 cells/mL, the defined reference range for the CCHMC clinical laboratory.

Data Analysis

Continuous variables were described using median and interquartile range (IQR) and compared across groups using Wilcoxon rank sum test due to non‐normal distributions. Categorical variables were described by counts and frequencies and compared using the 2 test.

Multivariable linear regression analysis was performed to assess the independent effect of receipt of empiric guideline‐recommended antibiotic therapy on outcomes of LOS and costs while adjusting for covariates. As LOS and costs were non‐normally distributed, we logarithmically transformed these values to use as the dependent variables in our models. The resulting coefficients were back‐transformed to reflect the percent change in LOS and costs incurred between subjects who received empiric guideline therapy compared with those who did not.[14] Covariates were chosen a priori due to their clinical and biological relevance to the outcomes of LOS (eg, wheezing on presentation and need for supplemental oxygen), total cost of hospitalization (eg, LOS and need for repeat imaging), and inpatient pharmacy costs (eg, LOS and wheezing on presentation) (Table 1).

Cohort Characteristics
CharacteristicOverall Cohort, n=220Guideline Therapy, n=166Nonguideline Therapy, n=54P Value
  • NOTE: Abbreviations: CT, computed tomography; IQR, interquartile range; PEWS, Pediatric Early Warning Scale. *P<0.05.

Age, y, median (IQR)2.9 (1.36.3)2.5 (1.35.2)5.6 (2.38.8)<0.01*
Male, no. (%)122 (55.5%)89 (53.6%)33 (61.1%)0.34
Emergency Severity Index, no. (%)0.11
290 (40.9%)73 (44.0%)17 (31.5%) 
3116 (52.7%)85 (51.2%)31 (57.4%) 
414 (6.4%)8 (4.8%)6 (11.1%) 
Abnormal vital signs on presentation, no. (%)
Fever99 (45.0%)80 (48.2%)19 (35.2%)0.10
Tachycardia100 (45.5%)76 (45.8%)24 (44.4%)0.86
Tachypnea124 (56.4%)100 (60.2%)24 (44.4%)0.04*
Hypotension000 
Hypoxia27 (12.3%)24 (14.5%)3 (5.6%)0.08
Physical exam on presentation, no. (%)
Increased respiratory effort146 (66.4%)111 (66.9%)35 (64.8%)0.78
Distressed110 (50.0%)86 (51.8%)24 (44.4%)0.35
Retraction103 (46.8%)81 (48.8%)22 (40.7%)0.30
Grunting17 (7.7%)14 (8.4%)3 (5.6%)0.49
Nasal flaring19 (8.6%)17 (10.2%)2 (3.7%)0.14
Rales135 (61.4%)99 (59.6%)36 (66.7%)0.36
Wheeze91 (41.4%)66 (39.8%)25 (46.3%)0.40
Decreased breath sounds89 (40.5%)65 (39.2%)24 (44.4%)0.49
Dehydration21 (9.6%)13 (7.8%)8 (14.8%)0.13
PEWS 5 during admission, no. (%)43 (19.6%)34 (20.5%)9 (16.7%)0.54
Oxygen requirement in first 24 hours, no. (%)114 (51.8%)90 (53.6%)24 (46.2%)0.35
Complete blood count obtained, no. (%)99 (45.0%)72 (43.4%)27 (50.0%)0.40
Abnormal white blood cell count35 (35.7%)23 (32.4%)12 (44.4%)0.27
Blood culture obtained, no. (%)104 (47.3%)80 (48.2%)24 (44.4%)0.63
Positive2 (1.9%)1 (1.3%)1 (4.2%)0.36
Chest radiograph available, no. (%)214 (97.3%)161 (97.0%)53 (98.2%)0.65
Infiltrate178 (83.2%)139 (86.3%)39 (73.6%)0.03*
Bilateral29 (16.3%)20 (14.4%)9 (23.1%)0.19
Multilobar46 (25.8%)33 (23.7%)13 (33.3%)0.23
Effusion24 (11.2%)16 (9.9%)8 (15.1%)0.30
Additional imaging, no. (%)    
Repeat chest radiograph26 (11.8%)17 (10.2%)9 (16.7%)0.20
Chest ultrasound4 (1.8%)3 (1.8%)1 (1.9%)0.98
Chest CT2 (0.9%)1 (0.6%)1 (1.9%)0.40
Antibiotic, no. (%)   <0.01*
Aminopenicillin140 (63.6%)140 (84.3%)0 (0%) 
Third‐generation cephalosporin37 (16.8%)8 (4.8%)29 (53.7%) 
Macrolide monotherapy18 (8.2%)0 (0%)18 (33.3%) 
Clindamycin2 (0.9%)1 (0.6%)1 (1.9%) 
Levofloxacin1 (0.5%)0 (0%)1 (1.9%) 
Aminopenicillin+macrolide16 (7.3%)16 (9.6%)0 (0%) 
Cephalosporin+macrolide6 (2.7%)1 (0.6%)5 (9.3%) 

Secondary outcomes of broadened antibiotic therapy, ED revisits, and hospital readmissions were assessed using the Fisher exact test. Due to the small number of events, we were unable to evaluate these associations in models adjusted for potential confounders.

All analyses were performed with SAS version 9.3 (SAS Institute, Cary, NC), and P values <0.05 were considered significant.

RESULTS

Of the 220 unique patients included, 122 (55%) were male. The median age was 2.9 years (IQR: 1.36.3 years). Empiric guideline‐recommended therapy was prescribed to 168 (76%) patients (Table 1). Aminopenicillins were the most common guideline‐recommended therapy, accounting for 84% of guideline‐recommended antibiotics. An additional 10% of patients received the guideline‐recommended combination therapy with an aminopenicillin and a macrolide. Nonguideline‐recommended therapy included third‐generation cephalosporin antibiotics (54%) and macrolide monotherapy (33%).

Those who received empiric guideline‐recommended antibiotic therapy were similar to those who received nonguideline‐recommended therapy with respect to sex, Emergency Severity Index, physical exam findings on presentation, oxygen requirement in the first 24 hours, abnormal laboratory findings, presence of effusion on chest radiograph, and need for additional imaging (Table 1). However, patients in the guideline‐recommended therapy group were significantly younger (median 2.5 years vs 5.6 years, P0.01), more likely to have elevated respiratory rate on presentation (60.2% vs 44.4%, P=0.04), and more likely to have an infiltrate on chest radiograph (86.3% vs 73.6%, P=0.03) (Table 1). Patients who received nonguideline‐recommended macrolide monotherapy had a median age of 7.4 years (IQR: 5.89.8 years).

Median hospital LOS for the total cohort was 1.3 days (IQR: 0.91.9 days) (Table 2). There were no differences in LOS between patients who received and did not receive guideline‐recommended therapy in the unadjusted or the adjusted model (Table 3).

Unadjusted Outcomes
OutcomeGuideline Therapy, n=166Nonguideline Therapy, n=54P Value
  • NOTE: Abbreviations: IQR, interquartile range.

Length of stay, d, median (IQR)1.3 (0.91.9)1.3 (0.92.0)0.74
Total costs, median, (IQR)$4118 ($2,647$6,004)$4045 ($2,829$6,200)0.44
Pharmacy total costs, median, (IQR)$84 ($40$179)$106 ($58$217)0.12
Broadened therapy, no. (%)10 (6.0%)4 (7.4%)0.75
Emergency department revisit, no. (%)7 (4.2%)2 (3.7%)1.00
Readmission, no. (%)1 (0.6%)1 (1.9%)0.43
Univariate and Multivariate Analyses of Receipt of Empiric Guideline‐Recommended Therapy With Length of Stay, Total Costs, and Pharmacy Costs
OutcomeUnadjusted Coefficient (95% CI)Adjusted Coefficient (95% CI)Adjusted % Change in Outcome (95% CI)*
  • NOTE: Abbreviations: CI, confidence interval. *Negative adjusted percent change indicates decrease in outcome associated with guideline‐recommended therapy; positive adjusted percent change indicates increase in outcome associated with guideline‐recommended therapy. Model is adjusted for age, fever on presentation, tachypnea on presentation, wheezing on presentation, need for supplemental oxygen, Pediatric Early Warning Score 5, chest radiograph findings, and need for repeat imaging. Model is adjusted for age, wheezing on presentation, need for supplemental oxygen, Pediatric Early Warning Score 5, need for repeat imaging, and length of stay. Model is adjusted for age, wheezing on presentation, and length of stay.

Length of stay0.06 (0.27 to 0.15)0.06 (0.25 to 0.12)5.8 (22.1 to 12.8)
Total costs0.18 (0.40 to 0.04)0.11 (0.32 to 0.09)10.9 (27.4 to 9.4)
Pharmacy total costs0.44 (0.46 to 0.02)0.16 (0.57 to 0.24)14.8 (43.4 to 27.1)

Median total costs of the index hospitalization for the total cohort were $4097 (IQR: $2657$6054), with median inpatient pharmacy costs of $92 (IQR: $40$183) (Table 2). There were no differences in total or inpatient pharmacy costs for patients who received guideline‐recommended therapy compared with those who did not in unadjusted or adjusted analyses. Fourteen patients (6.4%) had antibiotic therapy broadened during hospitalization, 10 were initially prescribed guideline‐recommended therapy, and 4 were initially prescribed nonguideline‐recommended therapy (Table 4).

Clinical Details of Patients Who Had Antibiotic Therapy Broadened During Initial Hospitalization
Initial TherapyReasons for Antibiotic Change Identified From Chart Review
Guideline=10Ampicillin to ceftriaxone:
1 patient with clinical worsening
1 patient with coincident urinary tract infection due to resistant organism
4 patients without evidence of clinical worsening or documentation of rationale
Addition of a macrolide:
3 patients without evidence of clinical worsening or documentation of rationale
Addition of clindamycin:
1 patient with clinical worsening
Nonguideline=4Ceftriaxone to clindamycin:
1 patient with clinical worsening
Addition of a macrolide:
1 patient with clinical worsening
1 patients without evidence of clinical worsening or documentation of rationale
Addition of clindamycin:
1 patient with clinical worsening

Of the 9 pneumonia‐related ED revisits within 30 days of discharge, 7 occurred in patients prescribed empiric guideline‐recommended therapy (Table 5). No ED revisit resulted in hospital readmission or antibiotic change related to pneumonia. Two ED revisits resulted in new antibiotic prescriptions for diagnoses other than pneumonia.

Clinical Details of Patients With an Emergency Department Revisit or Inpatient Readmission Following Index Hospitalization
RevisitInitial TherapyDay PostdischargeClinical Symptoms at Return VisitClinical DiagnosisAntibiotic Prescription
  • NOTE: Abbreviations: ED, emergency department; IV, intravenous.

EDGuideline3Poor oral intake and feverPneumoniaContinued prior antibiotic
EDGuideline8Recurrent cough and feverResolving pneumoniaContinued prior antibiotic
EDGuideline13Follow‐upResolved pneumoniaNo further antibiotic
EDGuideline16Increased work of breathingReactive airway diseaseNo antibiotic
EDGuideline20Persistent coughViral illnessNo antibiotic
EDGuideline22Recurrent cough and congestionSinusitisAugmentin
EDGuideline26Increased work of breathingReactive airway diseaseNo antibiotic
EDNonguideline16Recurrent feverAcute otitis mediaAmoxicillin
EDNonguideline20Recurrent cough and feverViral illnessNo antibiotic
AdmissionGuideline3Increased work of breathingPneumoniaIV ampicillin
AdmissionNonguideline9Refusal to take oral clindamycinPneumoniaIV clindamycin

Two patients were readmitted for a pneumonia‐related illness within 30 days of discharge; 1 had received guideline‐recommended therapy (Table 5). Both patients were directly admitted to the inpatient ward without an associated ED visit. Antibiotic class was not changed for either patient upon readmission, despite the decision to convert to intravenous form.

DISCUSSION

In this retrospective cohort study, patients who received empiric guideline‐recommended antibiotic therapy on admission for CAP had no difference in LOS, total cost of hospitalization, or inpatient pharmacy costs compared with those who received therapy that varied from guideline recommendations. Our study suggests that prescribing narrow‐spectrum therapy and, in some circumstances, combination therapy, as recommended by the 2011 PIDS/IDSA pneumonia guideline, did not result in negative unintended consequences.

In our study, children receiving guideline‐recommended therapy were younger, more likely to have elevated respiratory rate on presentation, and more likely to have an infiltrate on chest radiograph. We hypothesize the age difference is a reflection of common use of nonguideline macrolide monotherapy in the older, school‐age child, as macrolides are commonly used for coverage of Mycoplasma pneumonia in older children with CAP.[15] Children receiving macrolide monotherapy were older than those receiving guideline‐recommended therapy (median age of 7.4 years and 2.5 years, respectively). We also hypothesize that some providers may prescribe macrolide monotherapy to children deemed less ill than expected for CAP (eg, normal percutaneous oxygen saturation). This hypothesis is supported by the finding that 60% of patients who had a normal respiratory rate and received nonguideline therapy were prescribed macrolide monotherapy. We did control for the characteristics that varied between the two treatment groups in our models to eliminate potential confounding.

One prior study evaluated the effects of guideline implementation in CAP. In evaluation of a clinical practice guideline that recommended ampicillin as first‐line therapy for CAP, no significant difference was found following guideline introduction in the number of treatment failures (defined as the need to broaden therapy or development of complicated pneumonia within 48 hours or 30‐day inpatient readmission).[16] Our study builds on these findings by directly comparing outcomes between recipients of guideline and nonguideline therapy, which was not done in the prestudy or poststudy design of prior work.[16] We believe that classifying patients based on empiric therapy received rather than timing of guideline introduction thoroughly examines the effect of following guideline recommendations. Additionally, outcomes other than treatment failures were examined in our study including LOS, costs, and ED revisits.

Our results are similar to other observational studies that compared narrow‐ and broad‐spectrum antibiotics for children hospitalized with CAP. Using administrative data, Williams et al. found no significant difference in LOS or cost between narrow‐ and broad‐spectrum intravenous antibiotic recipients ages 6 months to 18 years at 43 children's hospitals.[17] Queen et al. compared narrow‐ and broad‐spectrum antibiotic therapy for children ages 2 months to 18 years at 4 children's hospitals.[18] Differences in average daily cost were not significant, but children who received narrow‐spectrum antibiotics had a significantly shorter LOS. Finally, an observational study of 319 Israeli children <2 years of age found no significant difference in duration of oxygen requirement, LOS, or need for change in antibiotic therapy between the 66 children prescribed aminopenicillins and the 253 children prescribed cefuroxime.[19] These studies suggest that prescribing narrow‐spectrum antimicrobial therapy, as per the guideline recommendations, results in similar outcomes to broad‐spectrum antimicrobial therapy.

Our study adds to prior studies that compared narrow‐ and broad‐spectrum therapy by comparing outcomes associated with guideline‐recommended therapy to nonguideline therapy. We considered antibiotic therapy as guideline recommended if appropriately chosen per the guideline, not just by simple classification of antibiotic. For example, the use of a cephalosporin in a patient with aminopenicillin allergy was considered guideline‐recommended therapy. We chose to classify the exposure of empiric antibiotic therapy in this manner to reflect true clinical application of the guideline, as not all children are able to receive aminopenicillins. Additionally, as our study stemmed from our prior improvement work aimed at increasing guideline adherent therapy,[7] we have a higher frequency of narrow‐spectrum antibiotic use than prior studies. In our study, almost two‐thirds of patients received narrow‐spectrum therapy, whereas narrow‐spectrum use in prior studies ranged from 10% to 33%.[17, 18, 19] Finally, we were able to confirm the diagnosis of pneumonia via medical record review and to adjust for severity of illness using clinical variables including vital signs, physical exam findings, and laboratory and radiologic study results.

This study must be interpreted in the context of several limitations. First, our study population was defined through discharge diagnosis codes, and therefore dependent on the accuracy of coding. However, we minimized potential for misclassification through use of a previously validated approach to identify patients with CAP and through medical record review to confirm the diagnosis. Second, we may be unable to detect very small differences in outcomes given limited power, specifically for outcomes of LOS, ED revisits, hospital readmissions, and need to broaden antibiotic therapy. Third, residual confounding may be present. Although we controlled for many clinical variables in our analyses, antibiotic prescribing practices may be influenced by unmeasured factors. The potential of system level confounding is mitigated by standardized care for patients with CAP at our institution. Prior system‐level changes using quality‐improvement science have resulted in a high level of adherence with guideline‐recommended antimicrobials as well as standardized medical discharge criteria.[7, 20] Additionally, nonmedical factors may influence LOS, limiting its use as an outcome measure. This limitation was minimized in our study by standardizing medical discharge criteria. Prior work at our institution demonstrated that the majority of patients, including those with CAP, were discharged within 2 hours of meeting medical discharge criteria.[20] Fourth, discharged patients who experienced adverse outcomes may have received care at a nearby adult emergency department or at their pediatrician's office. Although these events would not have been captured in our electronic health record, serious complications due to treatment failure (eg, empyema) would require hospitalization. As our hospital is the only children's hospital in the Greater Cincinnati metropolitan area, these patents would receive care at our institution. Therefore, any misclassification of revisits or readmissions is likely to be minimal. Finally, study patients were admitted to a large tertiary academic children's hospital, warranting further investigation to determine if these findings can be translated to smaller community settings.

In conclusion, receipt of guideline‐recommended antibiotic therapy for patients hospitalized with CAP was not associated with increases in LOS, total costs of hospitalization, or inpatient pharmacy costs. Our findings highlight the importance of changing antibiotic prescribing practices to reflect guideline recommendations, as there was no evidence of negative unintended consequences with our local practice change.

Acknowledgments

Disclosures: Dr. Ambroggio and Dr. Thomson were supported by funds from the NRSA T32HP10027‐14. Dr. Shah was supported by funds from NIAID K01A173729. The authors report no conflicts of interest.

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References
  1. Kronman MP, Hersh AL, Feng R, Huang YS, Lee GE, Shah SS. Ambulatory visit rates and antibiotic prescribing for children with pneumonia, 1994–2007. Pediatrics. 2011;127(3):411418.
  2. Lee GE, Lorch SA, Sheffler‐Collins S, Kronman MP, Shah SS. National hospitalization trends for pediatric pneumonia and associated complications. Pediatrics. 2010;126(2):204213.
  3. Keren R, Luan X, Localio R, et al. Prioritization of comparative effectiveness research topics in hospital pediatrics. Arch Pediatr Adolesc Med. 2012;166(12):11551164.
  4. Bradley JS, Byington CL, Shah SS, et al. The management of community‐acquired pneumonia in infants and children older than 3 months of age: clinical practice guidelines by the Pediatric Infectious Diseases Society and the Infectious Diseases Society of America. Clin Infect Dis. 2011;53(7):e25e76.
  5. Brogan TV, Hall M, Williams DJ, et al. Variability in processes of care and outcomes among children hospitalized with community‐acquired pneumonia. Pediatr Infect Dis J. 2012;31(10):10361041.
  6. Ross RK, Hersh AL, Kronman MP, et al. Impact of IDSA/PIDS guidelines on treatment of community‐acquired pneumonia in hospitalized children. Clin Infect Dis. 2014;58(6):834838.
  7. Ambroggio L, Thomson J, Murtagh Kurowski E, et al. Quality improvement methods increase appropriate antibiotic prescribing for childhood pneumonia. Pediatrics. 2013;131(5):e1623e1631.
  8. Williams DJ, Shah SS, Myers A, et al. Identifying pediatric community‐acquired pneumonia hospitalizations: accuracy of administrative billing codes. JAMA Pediatr. 2013;167(9):851858.
  9. Feudtner C, Hays RM, Haynes G, Geyer JR, Neff JM, Koepsell TD. Deaths attributed to pediatric complex chronic conditions: national trends and implications for supportive care services. Pediatrics. 2001;107(6):E99.
  10. Centers for Medicare 2011.
  11. Kleinman ME, Chameides L, Schexnayder SM, et al. Pediatric advanced life support: 2010 American Heart Association guidelines for cardiopulmonary resuscitation and emergency cardiovascular care. Pediatrics. 2010;126(5):e1361e1399.
  12. Tucker KM, Brewer TL, Baker RB, Demeritt B, Vossmeyer MT. Prospective evaluation of a pediatric inpatient early warning scoring system. J Spec Pediatr Nurs. 2009;14(2):7985.
  13. Vittinghoff E, Glidden DV, Shiboski SC, McCulloch CE. Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models. New York, NY: Springer; 2005.
  14. Biondi E, McCulloh R, Alverson B, Klein A, Dixon A. Treatment of mycoplasma pneumonia: a systematic review. Pediatrics. 2014;133(6):10811090.
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  17. Queen MA, Myers AL, Hall M, et al. Comparative effectiveness of empiric antibiotics for community‐acquired pneumonia. Pediatrics. 2014;133(1):e23e29.
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Community‐acquired pneumonia (CAP) is a common and serious infection in children. With more than 150,000 children requiring hospitalization annually, CAP is the fifth most prevalent and the second most costly diagnosis of all pediatric hospitalizations in the United States.[1, 2, 3]

In August 2011, the Pediatric Infectious Diseases Society (PIDS) and the Infectious Diseases Society of America (IDSA) published an evidence‐based guideline for the management of CAP in children. This guideline recommended that fully immunized children without underlying complications who require hospitalization receive an aminopenicillin as first‐line antibiotic therapy.[4] Additionally, the guideline recommends empirically adding a macrolide to an aminopenicillin when atypical pneumonia is a diagnostic consideration.

This recommendation was a substantial departure from practice for hospitals nationwide, as a multicenter study of children's hospitals (20052010) demonstrated that <10% of patients diagnosed with CAP received aminopenicillins as empiric therapy.[5] Since publication of the PIDS/IDSA guidelines, the use of aminopenicillins has increased significantly across institutions, but the majority of hospitalized patients still receive broad‐spectrum cephalosporin therapy for CAP.[6]

At baseline, 30% of patients hospitalized with CAP received guideline‐recommended antibiotic therapy at our institution. Through the use of quality‐improvement methods, the proportion of patients receiving guideline‐recommended therapy increased to 100%.[7] The objective of this study was to ensure that there were not unintended negative consequences to guideline implementation. Specifically, we sought to identify changes in length of stay (LOS), hospital costs, and treatment failures associated with use of guideline‐recommended antibiotic therapy for children hospitalized with uncomplicated CAP.

METHODS

Study Design and Study Population

This retrospective cohort study included children age 3 months to 18 years, hospitalized with CAP, between May 2, 2011 and July 30, 2012, at Cincinnati Children's Hospital Medical Center (CCHMC), a 512‐bed free‐standing children's hospital. The CCHMC Institutional Review Board approved this study with a waiver of informed consent.

Patients were eligible for inclusion if they were admitted to the hospital for inpatient or observation level care with a primary or secondary International Classification of Disease, 9th Revision discharge diagnosis code of pneumonia (480.02, 480.89, 481, 482.0, 482.30‐2, 482.41‐2, 482.83, 482.8990, 483.8, 484.3, 485, 486, 487.0) or effusion/empyema (510.0, 510.9, 511.01, 511.89, 513).[8] Patients with complex chronic conditions[9] were excluded. Medical records of eligible patients (n=260) were reviewed by 2 members of the study team to ensure that patients fell into the purview of the guideline. Patients who did not receive antibiotics (n=11) or for whom there was documented concern for aspiration (n=1) were excluded. Additionally, patients with immunodeficiency (n=1) or who had not received age‐appropriate vaccinations (n=2), and patients who required intensive care unit admission on presentation (n=17) or who had a complicated pneumonia, defined by presence of moderate or large pleural effusion at time of admission (n=8), were also excluded.[7] Finally, for patients with multiple pneumonia admissions, only the index visit was included; subsequent visits occurring within 30 days of discharge were considered readmissions.

Treatment Measure

The primary exposure of interest was empiric antibiotic therapy upon hospital admission. Antibiotic therapy was classified as guideline recommended or nonguideline recommended. Guideline‐recommended therapy was defined as follows:

  1. For children without drug allergies: ampicillin (200 mg/kg/day intravenously) or amoxicillin (90 mg/kg/day orally);
  2. For children with penicillin allergy: ceftriaxone (50100 mg/kg/day intravenously or intramuscularly) or cefdinir (14 mg/kg/day orally);
  3. For children with penicillin and cephalosporin allergy: clindamycin (40 mg/kg/day orally or intravenously); and
  4. Or azithromycin (10 mg/kg/day orally or intravenously on day 1) in combination with antibiotic category 1 or 2 or 3 above.

 

Outcome Measures

The primary outcomes examined were hospital LOS, total cost of hospitalization, and inpatient pharmacy costs. LOS was measured in hours and defined as the difference in time between departure from and arrival to the inpatient unit. Total cost of index hospitalization included both direct and indirect costs, obtained from the Centers for Medicare & Medicaid Services' Relative Value Units data for Current Procedural Terminology codes.[10]

Secondary outcomes included broadening of antibiotic therapy during the hospital course, pneumonia‐related emergency department (ED) revisits within 30 days, and pneumonia‐related inpatient readmissions within 30 days. Broadening of antibiotic therapy was defined as addition of a second antibiotic (eg, adding azithromycin on day 3 of hospitalization) or change in empiric antibiotic to a class with broader antimicrobial activity (eg, ampicillin to ceftriaxone) at any time during hospitalization. As our study population included only patients with uncomplicated pneumonia at the time of admission, this outcome was used to capture possible treatment failure. ED revisits and inpatient readmissions were reviewed by 3 investigators to identify pneumonia‐related visits. To encompass all possible treatment failures, all respiratory‐related complaints (eg, wheezing, respiratory distress) were considered as pneumonia‐related. Disagreements were resolved by group discussion.

Covariates

Severity of illness on presentation was evaluated using the Emergency Severity Index version 4,[11] abnormal vital signs on presentation (as defined by Pediatric Advanced Life Support age‐specific criteria[12]), and need for oxygen in the first 24 hours of hospitalization. Supplemental oxygen is administered for saturations <91% per protocol at our institution. The patient's highest Pediatric Early Warning Scale score[13] during hospitalization was used as a proxy for disease severity. Exam findings on presentation (eg, increased respiratory effort, rales, wheezing) were determined through chart review. Laboratory tests and radiologic imaging variables included complete blood cell count, blood culture, chest radiograph, chest ultrasound, and chest computed tomography. Abnormal white blood cell count was defined as <5000 or >15,000 cells/mL, the defined reference range for the CCHMC clinical laboratory.

Data Analysis

Continuous variables were described using median and interquartile range (IQR) and compared across groups using Wilcoxon rank sum test due to non‐normal distributions. Categorical variables were described by counts and frequencies and compared using the 2 test.

Multivariable linear regression analysis was performed to assess the independent effect of receipt of empiric guideline‐recommended antibiotic therapy on outcomes of LOS and costs while adjusting for covariates. As LOS and costs were non‐normally distributed, we logarithmically transformed these values to use as the dependent variables in our models. The resulting coefficients were back‐transformed to reflect the percent change in LOS and costs incurred between subjects who received empiric guideline therapy compared with those who did not.[14] Covariates were chosen a priori due to their clinical and biological relevance to the outcomes of LOS (eg, wheezing on presentation and need for supplemental oxygen), total cost of hospitalization (eg, LOS and need for repeat imaging), and inpatient pharmacy costs (eg, LOS and wheezing on presentation) (Table 1).

Cohort Characteristics
CharacteristicOverall Cohort, n=220Guideline Therapy, n=166Nonguideline Therapy, n=54P Value
  • NOTE: Abbreviations: CT, computed tomography; IQR, interquartile range; PEWS, Pediatric Early Warning Scale. *P<0.05.

Age, y, median (IQR)2.9 (1.36.3)2.5 (1.35.2)5.6 (2.38.8)<0.01*
Male, no. (%)122 (55.5%)89 (53.6%)33 (61.1%)0.34
Emergency Severity Index, no. (%)0.11
290 (40.9%)73 (44.0%)17 (31.5%) 
3116 (52.7%)85 (51.2%)31 (57.4%) 
414 (6.4%)8 (4.8%)6 (11.1%) 
Abnormal vital signs on presentation, no. (%)
Fever99 (45.0%)80 (48.2%)19 (35.2%)0.10
Tachycardia100 (45.5%)76 (45.8%)24 (44.4%)0.86
Tachypnea124 (56.4%)100 (60.2%)24 (44.4%)0.04*
Hypotension000 
Hypoxia27 (12.3%)24 (14.5%)3 (5.6%)0.08
Physical exam on presentation, no. (%)
Increased respiratory effort146 (66.4%)111 (66.9%)35 (64.8%)0.78
Distressed110 (50.0%)86 (51.8%)24 (44.4%)0.35
Retraction103 (46.8%)81 (48.8%)22 (40.7%)0.30
Grunting17 (7.7%)14 (8.4%)3 (5.6%)0.49
Nasal flaring19 (8.6%)17 (10.2%)2 (3.7%)0.14
Rales135 (61.4%)99 (59.6%)36 (66.7%)0.36
Wheeze91 (41.4%)66 (39.8%)25 (46.3%)0.40
Decreased breath sounds89 (40.5%)65 (39.2%)24 (44.4%)0.49
Dehydration21 (9.6%)13 (7.8%)8 (14.8%)0.13
PEWS 5 during admission, no. (%)43 (19.6%)34 (20.5%)9 (16.7%)0.54
Oxygen requirement in first 24 hours, no. (%)114 (51.8%)90 (53.6%)24 (46.2%)0.35
Complete blood count obtained, no. (%)99 (45.0%)72 (43.4%)27 (50.0%)0.40
Abnormal white blood cell count35 (35.7%)23 (32.4%)12 (44.4%)0.27
Blood culture obtained, no. (%)104 (47.3%)80 (48.2%)24 (44.4%)0.63
Positive2 (1.9%)1 (1.3%)1 (4.2%)0.36
Chest radiograph available, no. (%)214 (97.3%)161 (97.0%)53 (98.2%)0.65
Infiltrate178 (83.2%)139 (86.3%)39 (73.6%)0.03*
Bilateral29 (16.3%)20 (14.4%)9 (23.1%)0.19
Multilobar46 (25.8%)33 (23.7%)13 (33.3%)0.23
Effusion24 (11.2%)16 (9.9%)8 (15.1%)0.30
Additional imaging, no. (%)    
Repeat chest radiograph26 (11.8%)17 (10.2%)9 (16.7%)0.20
Chest ultrasound4 (1.8%)3 (1.8%)1 (1.9%)0.98
Chest CT2 (0.9%)1 (0.6%)1 (1.9%)0.40
Antibiotic, no. (%)   <0.01*
Aminopenicillin140 (63.6%)140 (84.3%)0 (0%) 
Third‐generation cephalosporin37 (16.8%)8 (4.8%)29 (53.7%) 
Macrolide monotherapy18 (8.2%)0 (0%)18 (33.3%) 
Clindamycin2 (0.9%)1 (0.6%)1 (1.9%) 
Levofloxacin1 (0.5%)0 (0%)1 (1.9%) 
Aminopenicillin+macrolide16 (7.3%)16 (9.6%)0 (0%) 
Cephalosporin+macrolide6 (2.7%)1 (0.6%)5 (9.3%) 

Secondary outcomes of broadened antibiotic therapy, ED revisits, and hospital readmissions were assessed using the Fisher exact test. Due to the small number of events, we were unable to evaluate these associations in models adjusted for potential confounders.

All analyses were performed with SAS version 9.3 (SAS Institute, Cary, NC), and P values <0.05 were considered significant.

RESULTS

Of the 220 unique patients included, 122 (55%) were male. The median age was 2.9 years (IQR: 1.36.3 years). Empiric guideline‐recommended therapy was prescribed to 168 (76%) patients (Table 1). Aminopenicillins were the most common guideline‐recommended therapy, accounting for 84% of guideline‐recommended antibiotics. An additional 10% of patients received the guideline‐recommended combination therapy with an aminopenicillin and a macrolide. Nonguideline‐recommended therapy included third‐generation cephalosporin antibiotics (54%) and macrolide monotherapy (33%).

Those who received empiric guideline‐recommended antibiotic therapy were similar to those who received nonguideline‐recommended therapy with respect to sex, Emergency Severity Index, physical exam findings on presentation, oxygen requirement in the first 24 hours, abnormal laboratory findings, presence of effusion on chest radiograph, and need for additional imaging (Table 1). However, patients in the guideline‐recommended therapy group were significantly younger (median 2.5 years vs 5.6 years, P0.01), more likely to have elevated respiratory rate on presentation (60.2% vs 44.4%, P=0.04), and more likely to have an infiltrate on chest radiograph (86.3% vs 73.6%, P=0.03) (Table 1). Patients who received nonguideline‐recommended macrolide monotherapy had a median age of 7.4 years (IQR: 5.89.8 years).

Median hospital LOS for the total cohort was 1.3 days (IQR: 0.91.9 days) (Table 2). There were no differences in LOS between patients who received and did not receive guideline‐recommended therapy in the unadjusted or the adjusted model (Table 3).

Unadjusted Outcomes
OutcomeGuideline Therapy, n=166Nonguideline Therapy, n=54P Value
  • NOTE: Abbreviations: IQR, interquartile range.

Length of stay, d, median (IQR)1.3 (0.91.9)1.3 (0.92.0)0.74
Total costs, median, (IQR)$4118 ($2,647$6,004)$4045 ($2,829$6,200)0.44
Pharmacy total costs, median, (IQR)$84 ($40$179)$106 ($58$217)0.12
Broadened therapy, no. (%)10 (6.0%)4 (7.4%)0.75
Emergency department revisit, no. (%)7 (4.2%)2 (3.7%)1.00
Readmission, no. (%)1 (0.6%)1 (1.9%)0.43
Univariate and Multivariate Analyses of Receipt of Empiric Guideline‐Recommended Therapy With Length of Stay, Total Costs, and Pharmacy Costs
OutcomeUnadjusted Coefficient (95% CI)Adjusted Coefficient (95% CI)Adjusted % Change in Outcome (95% CI)*
  • NOTE: Abbreviations: CI, confidence interval. *Negative adjusted percent change indicates decrease in outcome associated with guideline‐recommended therapy; positive adjusted percent change indicates increase in outcome associated with guideline‐recommended therapy. Model is adjusted for age, fever on presentation, tachypnea on presentation, wheezing on presentation, need for supplemental oxygen, Pediatric Early Warning Score 5, chest radiograph findings, and need for repeat imaging. Model is adjusted for age, wheezing on presentation, need for supplemental oxygen, Pediatric Early Warning Score 5, need for repeat imaging, and length of stay. Model is adjusted for age, wheezing on presentation, and length of stay.

Length of stay0.06 (0.27 to 0.15)0.06 (0.25 to 0.12)5.8 (22.1 to 12.8)
Total costs0.18 (0.40 to 0.04)0.11 (0.32 to 0.09)10.9 (27.4 to 9.4)
Pharmacy total costs0.44 (0.46 to 0.02)0.16 (0.57 to 0.24)14.8 (43.4 to 27.1)

Median total costs of the index hospitalization for the total cohort were $4097 (IQR: $2657$6054), with median inpatient pharmacy costs of $92 (IQR: $40$183) (Table 2). There were no differences in total or inpatient pharmacy costs for patients who received guideline‐recommended therapy compared with those who did not in unadjusted or adjusted analyses. Fourteen patients (6.4%) had antibiotic therapy broadened during hospitalization, 10 were initially prescribed guideline‐recommended therapy, and 4 were initially prescribed nonguideline‐recommended therapy (Table 4).

Clinical Details of Patients Who Had Antibiotic Therapy Broadened During Initial Hospitalization
Initial TherapyReasons for Antibiotic Change Identified From Chart Review
Guideline=10Ampicillin to ceftriaxone:
1 patient with clinical worsening
1 patient with coincident urinary tract infection due to resistant organism
4 patients without evidence of clinical worsening or documentation of rationale
Addition of a macrolide:
3 patients without evidence of clinical worsening or documentation of rationale
Addition of clindamycin:
1 patient with clinical worsening
Nonguideline=4Ceftriaxone to clindamycin:
1 patient with clinical worsening
Addition of a macrolide:
1 patient with clinical worsening
1 patients without evidence of clinical worsening or documentation of rationale
Addition of clindamycin:
1 patient with clinical worsening

Of the 9 pneumonia‐related ED revisits within 30 days of discharge, 7 occurred in patients prescribed empiric guideline‐recommended therapy (Table 5). No ED revisit resulted in hospital readmission or antibiotic change related to pneumonia. Two ED revisits resulted in new antibiotic prescriptions for diagnoses other than pneumonia.

Clinical Details of Patients With an Emergency Department Revisit or Inpatient Readmission Following Index Hospitalization
RevisitInitial TherapyDay PostdischargeClinical Symptoms at Return VisitClinical DiagnosisAntibiotic Prescription
  • NOTE: Abbreviations: ED, emergency department; IV, intravenous.

EDGuideline3Poor oral intake and feverPneumoniaContinued prior antibiotic
EDGuideline8Recurrent cough and feverResolving pneumoniaContinued prior antibiotic
EDGuideline13Follow‐upResolved pneumoniaNo further antibiotic
EDGuideline16Increased work of breathingReactive airway diseaseNo antibiotic
EDGuideline20Persistent coughViral illnessNo antibiotic
EDGuideline22Recurrent cough and congestionSinusitisAugmentin
EDGuideline26Increased work of breathingReactive airway diseaseNo antibiotic
EDNonguideline16Recurrent feverAcute otitis mediaAmoxicillin
EDNonguideline20Recurrent cough and feverViral illnessNo antibiotic
AdmissionGuideline3Increased work of breathingPneumoniaIV ampicillin
AdmissionNonguideline9Refusal to take oral clindamycinPneumoniaIV clindamycin

Two patients were readmitted for a pneumonia‐related illness within 30 days of discharge; 1 had received guideline‐recommended therapy (Table 5). Both patients were directly admitted to the inpatient ward without an associated ED visit. Antibiotic class was not changed for either patient upon readmission, despite the decision to convert to intravenous form.

DISCUSSION

In this retrospective cohort study, patients who received empiric guideline‐recommended antibiotic therapy on admission for CAP had no difference in LOS, total cost of hospitalization, or inpatient pharmacy costs compared with those who received therapy that varied from guideline recommendations. Our study suggests that prescribing narrow‐spectrum therapy and, in some circumstances, combination therapy, as recommended by the 2011 PIDS/IDSA pneumonia guideline, did not result in negative unintended consequences.

In our study, children receiving guideline‐recommended therapy were younger, more likely to have elevated respiratory rate on presentation, and more likely to have an infiltrate on chest radiograph. We hypothesize the age difference is a reflection of common use of nonguideline macrolide monotherapy in the older, school‐age child, as macrolides are commonly used for coverage of Mycoplasma pneumonia in older children with CAP.[15] Children receiving macrolide monotherapy were older than those receiving guideline‐recommended therapy (median age of 7.4 years and 2.5 years, respectively). We also hypothesize that some providers may prescribe macrolide monotherapy to children deemed less ill than expected for CAP (eg, normal percutaneous oxygen saturation). This hypothesis is supported by the finding that 60% of patients who had a normal respiratory rate and received nonguideline therapy were prescribed macrolide monotherapy. We did control for the characteristics that varied between the two treatment groups in our models to eliminate potential confounding.

One prior study evaluated the effects of guideline implementation in CAP. In evaluation of a clinical practice guideline that recommended ampicillin as first‐line therapy for CAP, no significant difference was found following guideline introduction in the number of treatment failures (defined as the need to broaden therapy or development of complicated pneumonia within 48 hours or 30‐day inpatient readmission).[16] Our study builds on these findings by directly comparing outcomes between recipients of guideline and nonguideline therapy, which was not done in the prestudy or poststudy design of prior work.[16] We believe that classifying patients based on empiric therapy received rather than timing of guideline introduction thoroughly examines the effect of following guideline recommendations. Additionally, outcomes other than treatment failures were examined in our study including LOS, costs, and ED revisits.

Our results are similar to other observational studies that compared narrow‐ and broad‐spectrum antibiotics for children hospitalized with CAP. Using administrative data, Williams et al. found no significant difference in LOS or cost between narrow‐ and broad‐spectrum intravenous antibiotic recipients ages 6 months to 18 years at 43 children's hospitals.[17] Queen et al. compared narrow‐ and broad‐spectrum antibiotic therapy for children ages 2 months to 18 years at 4 children's hospitals.[18] Differences in average daily cost were not significant, but children who received narrow‐spectrum antibiotics had a significantly shorter LOS. Finally, an observational study of 319 Israeli children <2 years of age found no significant difference in duration of oxygen requirement, LOS, or need for change in antibiotic therapy between the 66 children prescribed aminopenicillins and the 253 children prescribed cefuroxime.[19] These studies suggest that prescribing narrow‐spectrum antimicrobial therapy, as per the guideline recommendations, results in similar outcomes to broad‐spectrum antimicrobial therapy.

Our study adds to prior studies that compared narrow‐ and broad‐spectrum therapy by comparing outcomes associated with guideline‐recommended therapy to nonguideline therapy. We considered antibiotic therapy as guideline recommended if appropriately chosen per the guideline, not just by simple classification of antibiotic. For example, the use of a cephalosporin in a patient with aminopenicillin allergy was considered guideline‐recommended therapy. We chose to classify the exposure of empiric antibiotic therapy in this manner to reflect true clinical application of the guideline, as not all children are able to receive aminopenicillins. Additionally, as our study stemmed from our prior improvement work aimed at increasing guideline adherent therapy,[7] we have a higher frequency of narrow‐spectrum antibiotic use than prior studies. In our study, almost two‐thirds of patients received narrow‐spectrum therapy, whereas narrow‐spectrum use in prior studies ranged from 10% to 33%.[17, 18, 19] Finally, we were able to confirm the diagnosis of pneumonia via medical record review and to adjust for severity of illness using clinical variables including vital signs, physical exam findings, and laboratory and radiologic study results.

This study must be interpreted in the context of several limitations. First, our study population was defined through discharge diagnosis codes, and therefore dependent on the accuracy of coding. However, we minimized potential for misclassification through use of a previously validated approach to identify patients with CAP and through medical record review to confirm the diagnosis. Second, we may be unable to detect very small differences in outcomes given limited power, specifically for outcomes of LOS, ED revisits, hospital readmissions, and need to broaden antibiotic therapy. Third, residual confounding may be present. Although we controlled for many clinical variables in our analyses, antibiotic prescribing practices may be influenced by unmeasured factors. The potential of system level confounding is mitigated by standardized care for patients with CAP at our institution. Prior system‐level changes using quality‐improvement science have resulted in a high level of adherence with guideline‐recommended antimicrobials as well as standardized medical discharge criteria.[7, 20] Additionally, nonmedical factors may influence LOS, limiting its use as an outcome measure. This limitation was minimized in our study by standardizing medical discharge criteria. Prior work at our institution demonstrated that the majority of patients, including those with CAP, were discharged within 2 hours of meeting medical discharge criteria.[20] Fourth, discharged patients who experienced adverse outcomes may have received care at a nearby adult emergency department or at their pediatrician's office. Although these events would not have been captured in our electronic health record, serious complications due to treatment failure (eg, empyema) would require hospitalization. As our hospital is the only children's hospital in the Greater Cincinnati metropolitan area, these patents would receive care at our institution. Therefore, any misclassification of revisits or readmissions is likely to be minimal. Finally, study patients were admitted to a large tertiary academic children's hospital, warranting further investigation to determine if these findings can be translated to smaller community settings.

In conclusion, receipt of guideline‐recommended antibiotic therapy for patients hospitalized with CAP was not associated with increases in LOS, total costs of hospitalization, or inpatient pharmacy costs. Our findings highlight the importance of changing antibiotic prescribing practices to reflect guideline recommendations, as there was no evidence of negative unintended consequences with our local practice change.

Acknowledgments

Disclosures: Dr. Ambroggio and Dr. Thomson were supported by funds from the NRSA T32HP10027‐14. Dr. Shah was supported by funds from NIAID K01A173729. The authors report no conflicts of interest.

Community‐acquired pneumonia (CAP) is a common and serious infection in children. With more than 150,000 children requiring hospitalization annually, CAP is the fifth most prevalent and the second most costly diagnosis of all pediatric hospitalizations in the United States.[1, 2, 3]

In August 2011, the Pediatric Infectious Diseases Society (PIDS) and the Infectious Diseases Society of America (IDSA) published an evidence‐based guideline for the management of CAP in children. This guideline recommended that fully immunized children without underlying complications who require hospitalization receive an aminopenicillin as first‐line antibiotic therapy.[4] Additionally, the guideline recommends empirically adding a macrolide to an aminopenicillin when atypical pneumonia is a diagnostic consideration.

This recommendation was a substantial departure from practice for hospitals nationwide, as a multicenter study of children's hospitals (20052010) demonstrated that <10% of patients diagnosed with CAP received aminopenicillins as empiric therapy.[5] Since publication of the PIDS/IDSA guidelines, the use of aminopenicillins has increased significantly across institutions, but the majority of hospitalized patients still receive broad‐spectrum cephalosporin therapy for CAP.[6]

At baseline, 30% of patients hospitalized with CAP received guideline‐recommended antibiotic therapy at our institution. Through the use of quality‐improvement methods, the proportion of patients receiving guideline‐recommended therapy increased to 100%.[7] The objective of this study was to ensure that there were not unintended negative consequences to guideline implementation. Specifically, we sought to identify changes in length of stay (LOS), hospital costs, and treatment failures associated with use of guideline‐recommended antibiotic therapy for children hospitalized with uncomplicated CAP.

METHODS

Study Design and Study Population

This retrospective cohort study included children age 3 months to 18 years, hospitalized with CAP, between May 2, 2011 and July 30, 2012, at Cincinnati Children's Hospital Medical Center (CCHMC), a 512‐bed free‐standing children's hospital. The CCHMC Institutional Review Board approved this study with a waiver of informed consent.

Patients were eligible for inclusion if they were admitted to the hospital for inpatient or observation level care with a primary or secondary International Classification of Disease, 9th Revision discharge diagnosis code of pneumonia (480.02, 480.89, 481, 482.0, 482.30‐2, 482.41‐2, 482.83, 482.8990, 483.8, 484.3, 485, 486, 487.0) or effusion/empyema (510.0, 510.9, 511.01, 511.89, 513).[8] Patients with complex chronic conditions[9] were excluded. Medical records of eligible patients (n=260) were reviewed by 2 members of the study team to ensure that patients fell into the purview of the guideline. Patients who did not receive antibiotics (n=11) or for whom there was documented concern for aspiration (n=1) were excluded. Additionally, patients with immunodeficiency (n=1) or who had not received age‐appropriate vaccinations (n=2), and patients who required intensive care unit admission on presentation (n=17) or who had a complicated pneumonia, defined by presence of moderate or large pleural effusion at time of admission (n=8), were also excluded.[7] Finally, for patients with multiple pneumonia admissions, only the index visit was included; subsequent visits occurring within 30 days of discharge were considered readmissions.

Treatment Measure

The primary exposure of interest was empiric antibiotic therapy upon hospital admission. Antibiotic therapy was classified as guideline recommended or nonguideline recommended. Guideline‐recommended therapy was defined as follows:

  1. For children without drug allergies: ampicillin (200 mg/kg/day intravenously) or amoxicillin (90 mg/kg/day orally);
  2. For children with penicillin allergy: ceftriaxone (50100 mg/kg/day intravenously or intramuscularly) or cefdinir (14 mg/kg/day orally);
  3. For children with penicillin and cephalosporin allergy: clindamycin (40 mg/kg/day orally or intravenously); and
  4. Or azithromycin (10 mg/kg/day orally or intravenously on day 1) in combination with antibiotic category 1 or 2 or 3 above.

 

Outcome Measures

The primary outcomes examined were hospital LOS, total cost of hospitalization, and inpatient pharmacy costs. LOS was measured in hours and defined as the difference in time between departure from and arrival to the inpatient unit. Total cost of index hospitalization included both direct and indirect costs, obtained from the Centers for Medicare & Medicaid Services' Relative Value Units data for Current Procedural Terminology codes.[10]

Secondary outcomes included broadening of antibiotic therapy during the hospital course, pneumonia‐related emergency department (ED) revisits within 30 days, and pneumonia‐related inpatient readmissions within 30 days. Broadening of antibiotic therapy was defined as addition of a second antibiotic (eg, adding azithromycin on day 3 of hospitalization) or change in empiric antibiotic to a class with broader antimicrobial activity (eg, ampicillin to ceftriaxone) at any time during hospitalization. As our study population included only patients with uncomplicated pneumonia at the time of admission, this outcome was used to capture possible treatment failure. ED revisits and inpatient readmissions were reviewed by 3 investigators to identify pneumonia‐related visits. To encompass all possible treatment failures, all respiratory‐related complaints (eg, wheezing, respiratory distress) were considered as pneumonia‐related. Disagreements were resolved by group discussion.

Covariates

Severity of illness on presentation was evaluated using the Emergency Severity Index version 4,[11] abnormal vital signs on presentation (as defined by Pediatric Advanced Life Support age‐specific criteria[12]), and need for oxygen in the first 24 hours of hospitalization. Supplemental oxygen is administered for saturations <91% per protocol at our institution. The patient's highest Pediatric Early Warning Scale score[13] during hospitalization was used as a proxy for disease severity. Exam findings on presentation (eg, increased respiratory effort, rales, wheezing) were determined through chart review. Laboratory tests and radiologic imaging variables included complete blood cell count, blood culture, chest radiograph, chest ultrasound, and chest computed tomography. Abnormal white blood cell count was defined as <5000 or >15,000 cells/mL, the defined reference range for the CCHMC clinical laboratory.

Data Analysis

Continuous variables were described using median and interquartile range (IQR) and compared across groups using Wilcoxon rank sum test due to non‐normal distributions. Categorical variables were described by counts and frequencies and compared using the 2 test.

Multivariable linear regression analysis was performed to assess the independent effect of receipt of empiric guideline‐recommended antibiotic therapy on outcomes of LOS and costs while adjusting for covariates. As LOS and costs were non‐normally distributed, we logarithmically transformed these values to use as the dependent variables in our models. The resulting coefficients were back‐transformed to reflect the percent change in LOS and costs incurred between subjects who received empiric guideline therapy compared with those who did not.[14] Covariates were chosen a priori due to their clinical and biological relevance to the outcomes of LOS (eg, wheezing on presentation and need for supplemental oxygen), total cost of hospitalization (eg, LOS and need for repeat imaging), and inpatient pharmacy costs (eg, LOS and wheezing on presentation) (Table 1).

Cohort Characteristics
CharacteristicOverall Cohort, n=220Guideline Therapy, n=166Nonguideline Therapy, n=54P Value
  • NOTE: Abbreviations: CT, computed tomography; IQR, interquartile range; PEWS, Pediatric Early Warning Scale. *P<0.05.

Age, y, median (IQR)2.9 (1.36.3)2.5 (1.35.2)5.6 (2.38.8)<0.01*
Male, no. (%)122 (55.5%)89 (53.6%)33 (61.1%)0.34
Emergency Severity Index, no. (%)0.11
290 (40.9%)73 (44.0%)17 (31.5%) 
3116 (52.7%)85 (51.2%)31 (57.4%) 
414 (6.4%)8 (4.8%)6 (11.1%) 
Abnormal vital signs on presentation, no. (%)
Fever99 (45.0%)80 (48.2%)19 (35.2%)0.10
Tachycardia100 (45.5%)76 (45.8%)24 (44.4%)0.86
Tachypnea124 (56.4%)100 (60.2%)24 (44.4%)0.04*
Hypotension000 
Hypoxia27 (12.3%)24 (14.5%)3 (5.6%)0.08
Physical exam on presentation, no. (%)
Increased respiratory effort146 (66.4%)111 (66.9%)35 (64.8%)0.78
Distressed110 (50.0%)86 (51.8%)24 (44.4%)0.35
Retraction103 (46.8%)81 (48.8%)22 (40.7%)0.30
Grunting17 (7.7%)14 (8.4%)3 (5.6%)0.49
Nasal flaring19 (8.6%)17 (10.2%)2 (3.7%)0.14
Rales135 (61.4%)99 (59.6%)36 (66.7%)0.36
Wheeze91 (41.4%)66 (39.8%)25 (46.3%)0.40
Decreased breath sounds89 (40.5%)65 (39.2%)24 (44.4%)0.49
Dehydration21 (9.6%)13 (7.8%)8 (14.8%)0.13
PEWS 5 during admission, no. (%)43 (19.6%)34 (20.5%)9 (16.7%)0.54
Oxygen requirement in first 24 hours, no. (%)114 (51.8%)90 (53.6%)24 (46.2%)0.35
Complete blood count obtained, no. (%)99 (45.0%)72 (43.4%)27 (50.0%)0.40
Abnormal white blood cell count35 (35.7%)23 (32.4%)12 (44.4%)0.27
Blood culture obtained, no. (%)104 (47.3%)80 (48.2%)24 (44.4%)0.63
Positive2 (1.9%)1 (1.3%)1 (4.2%)0.36
Chest radiograph available, no. (%)214 (97.3%)161 (97.0%)53 (98.2%)0.65
Infiltrate178 (83.2%)139 (86.3%)39 (73.6%)0.03*
Bilateral29 (16.3%)20 (14.4%)9 (23.1%)0.19
Multilobar46 (25.8%)33 (23.7%)13 (33.3%)0.23
Effusion24 (11.2%)16 (9.9%)8 (15.1%)0.30
Additional imaging, no. (%)    
Repeat chest radiograph26 (11.8%)17 (10.2%)9 (16.7%)0.20
Chest ultrasound4 (1.8%)3 (1.8%)1 (1.9%)0.98
Chest CT2 (0.9%)1 (0.6%)1 (1.9%)0.40
Antibiotic, no. (%)   <0.01*
Aminopenicillin140 (63.6%)140 (84.3%)0 (0%) 
Third‐generation cephalosporin37 (16.8%)8 (4.8%)29 (53.7%) 
Macrolide monotherapy18 (8.2%)0 (0%)18 (33.3%) 
Clindamycin2 (0.9%)1 (0.6%)1 (1.9%) 
Levofloxacin1 (0.5%)0 (0%)1 (1.9%) 
Aminopenicillin+macrolide16 (7.3%)16 (9.6%)0 (0%) 
Cephalosporin+macrolide6 (2.7%)1 (0.6%)5 (9.3%) 

Secondary outcomes of broadened antibiotic therapy, ED revisits, and hospital readmissions were assessed using the Fisher exact test. Due to the small number of events, we were unable to evaluate these associations in models adjusted for potential confounders.

All analyses were performed with SAS version 9.3 (SAS Institute, Cary, NC), and P values <0.05 were considered significant.

RESULTS

Of the 220 unique patients included, 122 (55%) were male. The median age was 2.9 years (IQR: 1.36.3 years). Empiric guideline‐recommended therapy was prescribed to 168 (76%) patients (Table 1). Aminopenicillins were the most common guideline‐recommended therapy, accounting for 84% of guideline‐recommended antibiotics. An additional 10% of patients received the guideline‐recommended combination therapy with an aminopenicillin and a macrolide. Nonguideline‐recommended therapy included third‐generation cephalosporin antibiotics (54%) and macrolide monotherapy (33%).

Those who received empiric guideline‐recommended antibiotic therapy were similar to those who received nonguideline‐recommended therapy with respect to sex, Emergency Severity Index, physical exam findings on presentation, oxygen requirement in the first 24 hours, abnormal laboratory findings, presence of effusion on chest radiograph, and need for additional imaging (Table 1). However, patients in the guideline‐recommended therapy group were significantly younger (median 2.5 years vs 5.6 years, P0.01), more likely to have elevated respiratory rate on presentation (60.2% vs 44.4%, P=0.04), and more likely to have an infiltrate on chest radiograph (86.3% vs 73.6%, P=0.03) (Table 1). Patients who received nonguideline‐recommended macrolide monotherapy had a median age of 7.4 years (IQR: 5.89.8 years).

Median hospital LOS for the total cohort was 1.3 days (IQR: 0.91.9 days) (Table 2). There were no differences in LOS between patients who received and did not receive guideline‐recommended therapy in the unadjusted or the adjusted model (Table 3).

Unadjusted Outcomes
OutcomeGuideline Therapy, n=166Nonguideline Therapy, n=54P Value
  • NOTE: Abbreviations: IQR, interquartile range.

Length of stay, d, median (IQR)1.3 (0.91.9)1.3 (0.92.0)0.74
Total costs, median, (IQR)$4118 ($2,647$6,004)$4045 ($2,829$6,200)0.44
Pharmacy total costs, median, (IQR)$84 ($40$179)$106 ($58$217)0.12
Broadened therapy, no. (%)10 (6.0%)4 (7.4%)0.75
Emergency department revisit, no. (%)7 (4.2%)2 (3.7%)1.00
Readmission, no. (%)1 (0.6%)1 (1.9%)0.43
Univariate and Multivariate Analyses of Receipt of Empiric Guideline‐Recommended Therapy With Length of Stay, Total Costs, and Pharmacy Costs
OutcomeUnadjusted Coefficient (95% CI)Adjusted Coefficient (95% CI)Adjusted % Change in Outcome (95% CI)*
  • NOTE: Abbreviations: CI, confidence interval. *Negative adjusted percent change indicates decrease in outcome associated with guideline‐recommended therapy; positive adjusted percent change indicates increase in outcome associated with guideline‐recommended therapy. Model is adjusted for age, fever on presentation, tachypnea on presentation, wheezing on presentation, need for supplemental oxygen, Pediatric Early Warning Score 5, chest radiograph findings, and need for repeat imaging. Model is adjusted for age, wheezing on presentation, need for supplemental oxygen, Pediatric Early Warning Score 5, need for repeat imaging, and length of stay. Model is adjusted for age, wheezing on presentation, and length of stay.

Length of stay0.06 (0.27 to 0.15)0.06 (0.25 to 0.12)5.8 (22.1 to 12.8)
Total costs0.18 (0.40 to 0.04)0.11 (0.32 to 0.09)10.9 (27.4 to 9.4)
Pharmacy total costs0.44 (0.46 to 0.02)0.16 (0.57 to 0.24)14.8 (43.4 to 27.1)

Median total costs of the index hospitalization for the total cohort were $4097 (IQR: $2657$6054), with median inpatient pharmacy costs of $92 (IQR: $40$183) (Table 2). There were no differences in total or inpatient pharmacy costs for patients who received guideline‐recommended therapy compared with those who did not in unadjusted or adjusted analyses. Fourteen patients (6.4%) had antibiotic therapy broadened during hospitalization, 10 were initially prescribed guideline‐recommended therapy, and 4 were initially prescribed nonguideline‐recommended therapy (Table 4).

Clinical Details of Patients Who Had Antibiotic Therapy Broadened During Initial Hospitalization
Initial TherapyReasons for Antibiotic Change Identified From Chart Review
Guideline=10Ampicillin to ceftriaxone:
1 patient with clinical worsening
1 patient with coincident urinary tract infection due to resistant organism
4 patients without evidence of clinical worsening or documentation of rationale
Addition of a macrolide:
3 patients without evidence of clinical worsening or documentation of rationale
Addition of clindamycin:
1 patient with clinical worsening
Nonguideline=4Ceftriaxone to clindamycin:
1 patient with clinical worsening
Addition of a macrolide:
1 patient with clinical worsening
1 patients without evidence of clinical worsening or documentation of rationale
Addition of clindamycin:
1 patient with clinical worsening

Of the 9 pneumonia‐related ED revisits within 30 days of discharge, 7 occurred in patients prescribed empiric guideline‐recommended therapy (Table 5). No ED revisit resulted in hospital readmission or antibiotic change related to pneumonia. Two ED revisits resulted in new antibiotic prescriptions for diagnoses other than pneumonia.

Clinical Details of Patients With an Emergency Department Revisit or Inpatient Readmission Following Index Hospitalization
RevisitInitial TherapyDay PostdischargeClinical Symptoms at Return VisitClinical DiagnosisAntibiotic Prescription
  • NOTE: Abbreviations: ED, emergency department; IV, intravenous.

EDGuideline3Poor oral intake and feverPneumoniaContinued prior antibiotic
EDGuideline8Recurrent cough and feverResolving pneumoniaContinued prior antibiotic
EDGuideline13Follow‐upResolved pneumoniaNo further antibiotic
EDGuideline16Increased work of breathingReactive airway diseaseNo antibiotic
EDGuideline20Persistent coughViral illnessNo antibiotic
EDGuideline22Recurrent cough and congestionSinusitisAugmentin
EDGuideline26Increased work of breathingReactive airway diseaseNo antibiotic
EDNonguideline16Recurrent feverAcute otitis mediaAmoxicillin
EDNonguideline20Recurrent cough and feverViral illnessNo antibiotic
AdmissionGuideline3Increased work of breathingPneumoniaIV ampicillin
AdmissionNonguideline9Refusal to take oral clindamycinPneumoniaIV clindamycin

Two patients were readmitted for a pneumonia‐related illness within 30 days of discharge; 1 had received guideline‐recommended therapy (Table 5). Both patients were directly admitted to the inpatient ward without an associated ED visit. Antibiotic class was not changed for either patient upon readmission, despite the decision to convert to intravenous form.

DISCUSSION

In this retrospective cohort study, patients who received empiric guideline‐recommended antibiotic therapy on admission for CAP had no difference in LOS, total cost of hospitalization, or inpatient pharmacy costs compared with those who received therapy that varied from guideline recommendations. Our study suggests that prescribing narrow‐spectrum therapy and, in some circumstances, combination therapy, as recommended by the 2011 PIDS/IDSA pneumonia guideline, did not result in negative unintended consequences.

In our study, children receiving guideline‐recommended therapy were younger, more likely to have elevated respiratory rate on presentation, and more likely to have an infiltrate on chest radiograph. We hypothesize the age difference is a reflection of common use of nonguideline macrolide monotherapy in the older, school‐age child, as macrolides are commonly used for coverage of Mycoplasma pneumonia in older children with CAP.[15] Children receiving macrolide monotherapy were older than those receiving guideline‐recommended therapy (median age of 7.4 years and 2.5 years, respectively). We also hypothesize that some providers may prescribe macrolide monotherapy to children deemed less ill than expected for CAP (eg, normal percutaneous oxygen saturation). This hypothesis is supported by the finding that 60% of patients who had a normal respiratory rate and received nonguideline therapy were prescribed macrolide monotherapy. We did control for the characteristics that varied between the two treatment groups in our models to eliminate potential confounding.

One prior study evaluated the effects of guideline implementation in CAP. In evaluation of a clinical practice guideline that recommended ampicillin as first‐line therapy for CAP, no significant difference was found following guideline introduction in the number of treatment failures (defined as the need to broaden therapy or development of complicated pneumonia within 48 hours or 30‐day inpatient readmission).[16] Our study builds on these findings by directly comparing outcomes between recipients of guideline and nonguideline therapy, which was not done in the prestudy or poststudy design of prior work.[16] We believe that classifying patients based on empiric therapy received rather than timing of guideline introduction thoroughly examines the effect of following guideline recommendations. Additionally, outcomes other than treatment failures were examined in our study including LOS, costs, and ED revisits.

Our results are similar to other observational studies that compared narrow‐ and broad‐spectrum antibiotics for children hospitalized with CAP. Using administrative data, Williams et al. found no significant difference in LOS or cost between narrow‐ and broad‐spectrum intravenous antibiotic recipients ages 6 months to 18 years at 43 children's hospitals.[17] Queen et al. compared narrow‐ and broad‐spectrum antibiotic therapy for children ages 2 months to 18 years at 4 children's hospitals.[18] Differences in average daily cost were not significant, but children who received narrow‐spectrum antibiotics had a significantly shorter LOS. Finally, an observational study of 319 Israeli children <2 years of age found no significant difference in duration of oxygen requirement, LOS, or need for change in antibiotic therapy between the 66 children prescribed aminopenicillins and the 253 children prescribed cefuroxime.[19] These studies suggest that prescribing narrow‐spectrum antimicrobial therapy, as per the guideline recommendations, results in similar outcomes to broad‐spectrum antimicrobial therapy.

Our study adds to prior studies that compared narrow‐ and broad‐spectrum therapy by comparing outcomes associated with guideline‐recommended therapy to nonguideline therapy. We considered antibiotic therapy as guideline recommended if appropriately chosen per the guideline, not just by simple classification of antibiotic. For example, the use of a cephalosporin in a patient with aminopenicillin allergy was considered guideline‐recommended therapy. We chose to classify the exposure of empiric antibiotic therapy in this manner to reflect true clinical application of the guideline, as not all children are able to receive aminopenicillins. Additionally, as our study stemmed from our prior improvement work aimed at increasing guideline adherent therapy,[7] we have a higher frequency of narrow‐spectrum antibiotic use than prior studies. In our study, almost two‐thirds of patients received narrow‐spectrum therapy, whereas narrow‐spectrum use in prior studies ranged from 10% to 33%.[17, 18, 19] Finally, we were able to confirm the diagnosis of pneumonia via medical record review and to adjust for severity of illness using clinical variables including vital signs, physical exam findings, and laboratory and radiologic study results.

This study must be interpreted in the context of several limitations. First, our study population was defined through discharge diagnosis codes, and therefore dependent on the accuracy of coding. However, we minimized potential for misclassification through use of a previously validated approach to identify patients with CAP and through medical record review to confirm the diagnosis. Second, we may be unable to detect very small differences in outcomes given limited power, specifically for outcomes of LOS, ED revisits, hospital readmissions, and need to broaden antibiotic therapy. Third, residual confounding may be present. Although we controlled for many clinical variables in our analyses, antibiotic prescribing practices may be influenced by unmeasured factors. The potential of system level confounding is mitigated by standardized care for patients with CAP at our institution. Prior system‐level changes using quality‐improvement science have resulted in a high level of adherence with guideline‐recommended antimicrobials as well as standardized medical discharge criteria.[7, 20] Additionally, nonmedical factors may influence LOS, limiting its use as an outcome measure. This limitation was minimized in our study by standardizing medical discharge criteria. Prior work at our institution demonstrated that the majority of patients, including those with CAP, were discharged within 2 hours of meeting medical discharge criteria.[20] Fourth, discharged patients who experienced adverse outcomes may have received care at a nearby adult emergency department or at their pediatrician's office. Although these events would not have been captured in our electronic health record, serious complications due to treatment failure (eg, empyema) would require hospitalization. As our hospital is the only children's hospital in the Greater Cincinnati metropolitan area, these patents would receive care at our institution. Therefore, any misclassification of revisits or readmissions is likely to be minimal. Finally, study patients were admitted to a large tertiary academic children's hospital, warranting further investigation to determine if these findings can be translated to smaller community settings.

In conclusion, receipt of guideline‐recommended antibiotic therapy for patients hospitalized with CAP was not associated with increases in LOS, total costs of hospitalization, or inpatient pharmacy costs. Our findings highlight the importance of changing antibiotic prescribing practices to reflect guideline recommendations, as there was no evidence of negative unintended consequences with our local practice change.

Acknowledgments

Disclosures: Dr. Ambroggio and Dr. Thomson were supported by funds from the NRSA T32HP10027‐14. Dr. Shah was supported by funds from NIAID K01A173729. The authors report no conflicts of interest.

References
  1. Kronman MP, Hersh AL, Feng R, Huang YS, Lee GE, Shah SS. Ambulatory visit rates and antibiotic prescribing for children with pneumonia, 1994–2007. Pediatrics. 2011;127(3):411418.
  2. Lee GE, Lorch SA, Sheffler‐Collins S, Kronman MP, Shah SS. National hospitalization trends for pediatric pneumonia and associated complications. Pediatrics. 2010;126(2):204213.
  3. Keren R, Luan X, Localio R, et al. Prioritization of comparative effectiveness research topics in hospital pediatrics. Arch Pediatr Adolesc Med. 2012;166(12):11551164.
  4. Bradley JS, Byington CL, Shah SS, et al. The management of community‐acquired pneumonia in infants and children older than 3 months of age: clinical practice guidelines by the Pediatric Infectious Diseases Society and the Infectious Diseases Society of America. Clin Infect Dis. 2011;53(7):e25e76.
  5. Brogan TV, Hall M, Williams DJ, et al. Variability in processes of care and outcomes among children hospitalized with community‐acquired pneumonia. Pediatr Infect Dis J. 2012;31(10):10361041.
  6. Ross RK, Hersh AL, Kronman MP, et al. Impact of IDSA/PIDS guidelines on treatment of community‐acquired pneumonia in hospitalized children. Clin Infect Dis. 2014;58(6):834838.
  7. Ambroggio L, Thomson J, Murtagh Kurowski E, et al. Quality improvement methods increase appropriate antibiotic prescribing for childhood pneumonia. Pediatrics. 2013;131(5):e1623e1631.
  8. Williams DJ, Shah SS, Myers A, et al. Identifying pediatric community‐acquired pneumonia hospitalizations: accuracy of administrative billing codes. JAMA Pediatr. 2013;167(9):851858.
  9. Feudtner C, Hays RM, Haynes G, Geyer JR, Neff JM, Koepsell TD. Deaths attributed to pediatric complex chronic conditions: national trends and implications for supportive care services. Pediatrics. 2001;107(6):E99.
  10. Centers for Medicare 2011.
  11. Kleinman ME, Chameides L, Schexnayder SM, et al. Pediatric advanced life support: 2010 American Heart Association guidelines for cardiopulmonary resuscitation and emergency cardiovascular care. Pediatrics. 2010;126(5):e1361e1399.
  12. Tucker KM, Brewer TL, Baker RB, Demeritt B, Vossmeyer MT. Prospective evaluation of a pediatric inpatient early warning scoring system. J Spec Pediatr Nurs. 2009;14(2):7985.
  13. Vittinghoff E, Glidden DV, Shiboski SC, McCulloch CE. Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models. New York, NY: Springer; 2005.
  14. Biondi E, McCulloh R, Alverson B, Klein A, Dixon A. Treatment of mycoplasma pneumonia: a systematic review. Pediatrics. 2014;133(6):10811090.
  15. Newman RE, Hedican EB, Herigon JC, Williams DD, Williams AR, Newland JG. Impact of a guideline on management of children hospitalized with community‐acquired pneumonia. Pediatrics. 2012;129(3):e597e604.
  16. Williams DJ, Hall M, Shah SS, et al. Narrow vs broad‐spectrum antimicrobial therapy for children hospitalized with pneumonia. Pediatrics. 2013;132(5):e1141e1148.
  17. Queen MA, Myers AL, Hall M, et al. Comparative effectiveness of empiric antibiotics for community‐acquired pneumonia. Pediatrics. 2014;133(1):e23e29.
  18. Dinur‐Schejter Y, Cohen‐Cymberknoh M, Tenenbaum A, et al. Antibiotic treatment of children with community‐acquired pneumonia: comparison of penicillin or ampicillin versus cefuroxime. Pediatr Pulmonol. 2013;48(1):5258.
  19. White CM, Statile AM, White DL, et al. Using quality improvement to optimise paediatric discharge efficiency. BMJ Qual Saf. 2014;23(5):428436.
References
  1. Kronman MP, Hersh AL, Feng R, Huang YS, Lee GE, Shah SS. Ambulatory visit rates and antibiotic prescribing for children with pneumonia, 1994–2007. Pediatrics. 2011;127(3):411418.
  2. Lee GE, Lorch SA, Sheffler‐Collins S, Kronman MP, Shah SS. National hospitalization trends for pediatric pneumonia and associated complications. Pediatrics. 2010;126(2):204213.
  3. Keren R, Luan X, Localio R, et al. Prioritization of comparative effectiveness research topics in hospital pediatrics. Arch Pediatr Adolesc Med. 2012;166(12):11551164.
  4. Bradley JS, Byington CL, Shah SS, et al. The management of community‐acquired pneumonia in infants and children older than 3 months of age: clinical practice guidelines by the Pediatric Infectious Diseases Society and the Infectious Diseases Society of America. Clin Infect Dis. 2011;53(7):e25e76.
  5. Brogan TV, Hall M, Williams DJ, et al. Variability in processes of care and outcomes among children hospitalized with community‐acquired pneumonia. Pediatr Infect Dis J. 2012;31(10):10361041.
  6. Ross RK, Hersh AL, Kronman MP, et al. Impact of IDSA/PIDS guidelines on treatment of community‐acquired pneumonia in hospitalized children. Clin Infect Dis. 2014;58(6):834838.
  7. Ambroggio L, Thomson J, Murtagh Kurowski E, et al. Quality improvement methods increase appropriate antibiotic prescribing for childhood pneumonia. Pediatrics. 2013;131(5):e1623e1631.
  8. Williams DJ, Shah SS, Myers A, et al. Identifying pediatric community‐acquired pneumonia hospitalizations: accuracy of administrative billing codes. JAMA Pediatr. 2013;167(9):851858.
  9. Feudtner C, Hays RM, Haynes G, Geyer JR, Neff JM, Koepsell TD. Deaths attributed to pediatric complex chronic conditions: national trends and implications for supportive care services. Pediatrics. 2001;107(6):E99.
  10. Centers for Medicare 2011.
  11. Kleinman ME, Chameides L, Schexnayder SM, et al. Pediatric advanced life support: 2010 American Heart Association guidelines for cardiopulmonary resuscitation and emergency cardiovascular care. Pediatrics. 2010;126(5):e1361e1399.
  12. Tucker KM, Brewer TL, Baker RB, Demeritt B, Vossmeyer MT. Prospective evaluation of a pediatric inpatient early warning scoring system. J Spec Pediatr Nurs. 2009;14(2):7985.
  13. Vittinghoff E, Glidden DV, Shiboski SC, McCulloch CE. Regression Methods in Biostatistics: Linear, Logistic, Survival, and Repeated Measures Models. New York, NY: Springer; 2005.
  14. Biondi E, McCulloh R, Alverson B, Klein A, Dixon A. Treatment of mycoplasma pneumonia: a systematic review. Pediatrics. 2014;133(6):10811090.
  15. Newman RE, Hedican EB, Herigon JC, Williams DD, Williams AR, Newland JG. Impact of a guideline on management of children hospitalized with community‐acquired pneumonia. Pediatrics. 2012;129(3):e597e604.
  16. Williams DJ, Hall M, Shah SS, et al. Narrow vs broad‐spectrum antimicrobial therapy for children hospitalized with pneumonia. Pediatrics. 2013;132(5):e1141e1148.
  17. Queen MA, Myers AL, Hall M, et al. Comparative effectiveness of empiric antibiotics for community‐acquired pneumonia. Pediatrics. 2014;133(1):e23e29.
  18. Dinur‐Schejter Y, Cohen‐Cymberknoh M, Tenenbaum A, et al. Antibiotic treatment of children with community‐acquired pneumonia: comparison of penicillin or ampicillin versus cefuroxime. Pediatr Pulmonol. 2013;48(1):5258.
  19. White CM, Statile AM, White DL, et al. Using quality improvement to optimise paediatric discharge efficiency. BMJ Qual Saf. 2014;23(5):428436.
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Address for correspondence and reprint requests: Joanna Thomson, MD, Division of Hospital Medicine, Cincinnati Children's Hospital Medical Center, 3333 Burnet Avenue, ML 9016, Cincinnati, OH, 45220; Telephone: 513‐803‐8092; Fax: 13‐803‐9244; E‐mail: joanna.thomson@cchmc.org
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